Dollar Carry Trades Induced from Zero Interest Rates to Risk Financial Assets, Mediocre Cyclical United States Economic Growth with GDP Five Trillion Dollars below Trend in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Cyclically Stagnating Real Private Fixed Investment, Swelling Undistributed Corporate Profits, United States Terms of International Trade, United States Housing, United States House Prices, United States House Prices, World Cyclical Slow Growth, and Government Intervention in Globalization: Part III

 

Carlos M. Pelaez

 

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.

 

IA Mediocre Cyclical United States Economic Growth

            IA1 Stagnating Real Private Fixed Investment

            IA2 Swelling Undistributed Corporate Profits

IID United States Terms of International Trade

IIA United States Housing Collapse

            IIA1 Sales of New Houses

            IIA2 United States House Prices

III World Financial Turbulence

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

IIID Appendix on European Central Bank Large Scale Lender of Last Resort

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

 

II I United States Housing Collapse. Data and other information continue to provide depressed conditions in the US housing market in a longer perspective, with recent improvement at the margin. Table IIB-1 shows sales of new houses in the US at seasonally adjusted annual equivalent rate (SAAR). The US Census Bureau revised all seasonally-adjusted new house sales from 2014 to 2019 with the report for Apr 2019 on May 23, 2019 (https://www.census.gov/construction/nrs/pdf/newressales.pdf). The US Census Bureau revised all seasonally adjusted new house sales from 2015 to 2020 with the report of Apr 2020 on May 26, 2020 (https://www.census.gov/construction/nrs/pdf/newressales.pdf). House sales fell in 50 of 116 months from Jan 2011 to Aug 2020 with monthly declines of 5 in 2011, 4 in 2012, 5 in 2013, 6 in 2014, 3 in 2015, 7 in 2016, 5 in 2017, 7 in 2018, 5 in 2019 and 3 in 2020. In Jan-Apr 2012, house sales increased at the annual equivalent rate of 11.8 percent and at 22.3 percent in May-Sep 2012. There was significant strength in Sep-Dec 2011 with annual equivalent rate of 48.4 percent. Sales of new houses fell at 7.0 percent in Oct 2012 with increase of 9.5 percent in Nov 2012. Sales of new houses rebounded 11.8 percent in Jan 2013 with annual equivalent rate of 55.7 percent from Oct 2012 to Jan 2013 because of the increase at 11.8 percent in Jan 2013. New house sales decreased at annual equivalent 3.0 percent in Feb-Mar 2013. New house sales weakened, decreasing at 3.1 percent in annual equivalent from Apr to Dec 2013 with significant volatility illustrated by decline of 20.2 percent in Jul 2013 and increase of 10.2 percent in Oct 2013. New house sales fell 2.9 percent in Dec 2013. New house sales increased 2.3 percent in Jan 2014 and fell 5.2 percent in Feb 2014, decreasing 3.6 percent in Mar 2014. New house sales decreased 0.5 percent in Apr 2014 and increased 11.9 percent in May 2014. New house sales fell 7.3 percent in Jun 2014 and decreased 3.8 percent in Jul 2014. New house sales increased at 8.0 percent in Jan-Aug 2014. New house sales jumped 13.4 percent in Aug 2014 and increased 3.1 percent in Sep 2014. New House sales increased 1.3 percent in Oct 2014 and fell 7.1 percent in Nov 2014. House sales fell at the annual equivalent rate of 11.4 percent in Sep-Nov 2014. New house sales increased 12.4 percent in Dec 2014 and increased 3.6 percent in Jan 2015. Sales of new houses increased 4.9 percent in Feb

2015 and fell 11.1 percent in Mar 2015. House sales increased 4.6 percent in Apr 2015. The annual equivalent rate in Dec 2014-Apr 2015 was 35.7 percent. New house sales changed 0.0 percent in May 2015 and fell 4.4 percent in Jun 2015, increasing 5.4 percent in Jul 2015. New house sales fell at annual equivalent 3.1 percent in May-Jul 2015. New house sales increased 2.4 percent in Aug 2015 and fell 12.0 percent in Sep 2015. New house sales decreased at annual equivalent 46.5 percent in Aug-Sep 2015. New house sales increased 5.7 percent in Oct 2015 and increased 4.6 percent in Nov 2015, increasing 8.3 percent in Dec 2015. New house sales increased at the annual equivalent rate of 105.6 percent in Oct-Dec 2015. New house sales decreased 6.8 percent in Jan 2016 at the annual equivalent rate of minus 57.0 percent. New house sales increased 1.2 percent in Feb 2016 and increased 2.1 percent in Mar 2016. New house sales jumped at 8.6 percent in Apr 2016. New house sales increased at the annual equivalent rate of 58.5 percent in Feb-Apr 2016. New house sales decreased 1.9 percent in May 2016 and decreased 0.4 percent in Jun 2016. New house sales jumped 14.5 percent in Jul 2016.  New house sales increased at the annual equivalent rate of 56.7 percent in May-Jul 2016. New house sales fell 8.6 percent in Aug 2016 and decreased 2.9 percent in Sep 2016, increasing 1.8 percent in Oct 2016. New house sales fell at the annual equivalent rate of minus 33.4 percent in Aug-Oct 2016. New house sales decreased at 1.0 percent in Nov 2016 and fell at 1.8 percent in Dec 2016. New house sales fell at 15.6 percent annual equivalent in Nov-Dec 2016. New house sales increased at 4.3 percent in Jan 2017 and increased at 2.1 percent in Feb 2017. New house sales increased at 45.8 percent in Jan-Feb 2017. New house sales increased at 5.7 percent in Mar 2017 and fell at 6.7 percent in Apr 2017. New house sales decreased at annual equivalent 8.0 percent in Mar-Apr 2017.  New house sales increased at 4.1 percent in May 2017 and increased at 1.1 percent in Jun 2017. New house sales increased at annual equivalent 35.9 percent in May-Jun 2017. New house sales decreased at 8.9 percent in Jul 2017 and decreased at 0.9 percent in Aug 2017, increasing at 13.9 percent in Sep 2017. New house sales increased at annual equivalent 11.8 percent in Jul-Sep 2017. New house sales decreased at 1.7 percent in Oct 2017. New house sales increased at 13.6 percent in Nov 2017. New house sales increased at annual equivalent 93.9 percent in Oct-Nov 2017. New house sales decreased at 7.7 percent in Dec 2017 and decreased at 5.3 percent in Jan 2018.  New house sales decreased at annual equivalent 55.4 percent in Dec 2017-Jan 2018. New house sales increased at 2.4 percent in Feb 2018, increasing at 3.9 percent in Mar 2018. New house sales increased at 45.0 percent in Feb-Mar 2018. New house sales decreased at 3.8 percent in Apr 2018 and increased at 3.1 percent in May 2018.  New House sales decreased at annual equivalent 4.8 percent in Apr-May 2018. New house sales decreased at 6.7 percent in Jun 2018 and increased at 0.7 percent in Jul 2018. New House sales decreased at annual equivalent 31.2 percent in Jun-Jul 2018. New house sales decreased at 3.1 percent in Aug 2018 and decreased at 0.3 percent in Sep 2018. New house sales decreased at annual equivalent 18.7 percent in Aug-Sep 2018. New house sales fell at 7.4 percent in Oct 2018 and increased at 11.2 percent in Nov 2018. New house sales increased at annual equivalent 19.2 percent in Oct-Nov 2018.  New house sales decreased at 8.1 percent in Dec 2018 and increased at 12.9 percent in Jan 2019. New House sales increased at annual equivalent 24.8 percent in Dec 2018-Jan 2019. New house sales increased at 4.4 percent in Feb 2019 and increased at 5.3 percent in Mar 2019. New house sales increased at annual equivalent 76.5 percent in Feb-Mar 2019. New house sales fell at 5.1 percent in Apr 2019 and fell at 9.6 percent in May 2019. New house sales decreased at annual equivalent 60.1 percent in Apr-May 2019. New house sales increased at 21.0 percent in Jun 2019 and decreased at 9.0 percent in Jul 2019. New house sales increased at annual equivalent 78.2 percent in Jun-Jul 2019. New house sales increased at 6.8 percent in Aug 2019 and increased at 2.8 percent in Sep 2019. New house sales decreased at 2.8 percent in Oct 2019. New house sales increased at annual equivalent 29.7 percent in Aug-Oct 2019. New house sales decreased at 1.4 percent in Nov 2019. New house sales decreased at annual equivalent 15.6 percent in Nov 2019. New house sales increased at 5.0 percent in Dec 2019. New house sales increased at 5.9 percent in Jan 2020. New house sales increased at annual equivalent 89.0 percent in Dec 2019-Jan 2020. New house sales decreased at 7.5 percent in Feb 2020. New house sales decreased at 14.5 percent in Mar 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. New house sales decreased at 6.9 percent in Apr 2020. New house sales decreased at annual equivalent 70.6 percent in Feb-Apr 2020. New house sales increased at 22.5 percent in May 2020. New house sales increased at 20.5 percent in Jun 2020. New house sales increased at 14.7 percent in Jul 2020. New house sales increased at annual equivalent 721.8 percent in May-Jul 2020. New house sales increased at 4.8 percent in Aug 2020. New house sales increased at annual equivalent 75.5 percent in Aug 2020. There are wide monthly oscillations. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), analyze how builders have provided financial assistance to home buyers, including those short of cash and with weaker credit background, explaining the rise in new home sales and the highest gap between prices of new and existing houses. The 30-year conventional mortgage rate increased from 3.40 on Apr 25, 2013 to 4.58 percent on Aug 22, 2013 (http://www.federalreserve.gov/releases/h15/data.htm), which could also be a factor in recent weakness with improvement after the rate fell to 4.26 in Nov 2013. The conventional mortgage rate rose to 4.48 percent on Dec 26, 2013 and fell to 4.32 percent on Jan 30, 2014. The conventional mortgage rate increased to 4.37 percent on Feb 26, 2014 and 4.40 percent on Mar 27, 2014. The conventional mortgage rate fell to 4.14 percent on Apr 22, 2014, stabilizing at 4.14 on Jun 26, 2014. The conventional mortgage rate stood at 3.93 percent on Aug 20, 2015 and at 3.91 percent on Sep 17, 2015. The conventional mortgage rate was at 3.79 percent on Oct 22, 2015. The conventional mortgage rate was 3.97 percent on Nov 20, 2015. The conventional mortgage rate was 3.97 percent on Dec 18, 2015, and 3.92 percent on Jan 14, 2016. The conventional mortgage rate was 3.65 percent on Feb 19, 2016. The commercial mortgage rate was 3.73 percent on Mar 17, 2016 and 3.59 percent on Apr 21, 2016. The conventional mortgage rate was 3.58 on May 19, 2016. The conventional mortgage rate was 3.54 percent on Jun 19, 2016 and 3.45 percent on Jul 21, 2016. The conventional mortgage rate was 3.43 percent on Aug 18, 2016 and 3.48 percent on Sep 22, 2016. The conventional mortgage rate was 3.94 on Nov 17, 2016 and 4.30 percent on Dec 22.  The conventional mortgage rate was 4.19 percent on Jan 26, 2017 and 4.15 percent on Feb 17, 2017. The conventional mortgage rate was 4.1 percent on Mar 16, 2017. The conventional mortgage rate was 3.97 percent on Apr 20, 2017. The conventional mortgage rate was 4.05 percent on May 18, 2017. The conventional mortgage rate was 3.90 percent on Jun 22, 2017. The conventional mortgage rate was 3.96 percent on Jul 20, 2017. The conventional mortgage rate was 3.90 percent on Aug 18, 2017. The conventional mortgage rate was 3.83 percent on Sep 21, 2017. The conventional mortgage rate was 3.88 percent on Oct 20, 2017. The conventional mortgage rate was 3.92 percent on Nov 22, 2017 and 3.94 on Dec 21, 2017. The conventional mortgage rate was 4.04 percent on Jan 18, 2018. The conventional mortgage rate was 4.40 percent on Feb 22, 2018. The conventional rate was 4.43 percent on Mar 1, 2018. The conventional mortgage rate was 4.45 percent on Mar 22, 2018. The conventional mortgage rate was 4.47 on Apr 19, 2018. The conventional mortgage rate was 4.87 percent in May 31, 2018. The conventional mortgage rate was 4.57 percent on Jun 21, 2018. The conventional mortgage rate was 4.52 percent on Jul 19, 2018. The conventional mortgage rate was 4.53 percent on Aug 16, 2018. The conventional mortgage rate was 4.65 percent on Sep 20, 2018. The conventional mortgage rate was 4.85 percent on Oct 18, 2018. The conventional mortgage rate was 4.81 percent on Nov 21, 2018. The conventional mortgage rate was 4.35 percent in Feb 2019. The conventional mortgage rate was 4.41 percent on Mar 7, 2019. The conventional mortgage rate was 4.06 percent on Mar 28, 2019. The conventional mortgage rate was 4.12 percent on Apr 5, 2019. The conventional mortgage rate was at 4.06 percent on May 23, 2019. The conventional mortgage rate was 3.84 percent on Jun 20, 2019. The conventional mortgage rate was at 3.81 percent on Jul 18, 2019. The conventional mortgage rate was 3.60 on Aug 22, 2019. The conventional mortgage rate was 3.66 percent on Nov 21, 2019. The conventional mortgage rate was 3.74 percent on

Dec 26, 2019. The conventional mortgage rate was 3.60 on Jan 24, 2020. The conventional mortgage rate was 3.49 percent on Feb 21, 2020. The conventional mortgage rate was 3.65 percent on Mar 19, 2020. The conventional mortgage rate was 3.31 percent on Apr 16, 2020. The conventional mortgage rate was 3.24 percent on May 20, 2020. The conventional mortgage rate was 3.13 percent on Jun 19, 2020. The conventional mortgage rate was 3.01 percent on Jul 24, 2020. The conventional mortgage rate was 2.99 percent on Aug 21, 2020. The conventional mortgage rate was 2.9 percent on Sep 24, 2020. The conventional mortgage rate measured in a survey by Freddie Mac (http://www.freddiemac.com/pmms/  http://www.freddiemac.com/pmms/about-pmms.html) is the “interest rate a lender would charge to lend mortgage money to a qualified borrower.”

Table IIB-1, US, Sales of New Houses at Seasonally Adjusted (SA) Annual Equivalent Rate, Thousands and % 

	SA Annual Rate Thousands	∆%
Aug 2020	1011	4.8
AE ∆% Aug		75.5
Jul	965	14.7
Jun	841	20.5
May	698	22.5
AE ∆% May-Jul		721.8
Apr	570	-6.9
Mar	612	-14.5
Feb	716	-7.5
AE ∆% Feb-Apr		-70.6
Jan	774	5.9
Dec 2019	731	5.0
AE ∆% Dec-Jan		89.0
Nov	696	-1.4
AE ∆% Nov		-15.6
Oct	706	-2.8
Sep	726	2.8
Aug	706	6.8
AE ∆% Aug-Oct		29.7
Jul	661	-9.0
Jun	726	21.0
AE ∆% Jun-Jul		78.2
May	600	-9.6
Apr	664	-5.1
AE ∆% Apr-May		-60.1
Mar	700	5.3
Feb	665	4.4
AE ∆% Feb-Mar		76.5
Jan	637	12.9
Dec 2018	564	-8.1
AE ∆% Dec-Jan		24.8
Nov	614	11.2
Oct	552	-7.4
AE ∆% Oct-Nov		19.2
Sep	596	-0.3
Aug	598	-3.1
AE ∆% Aug-Sep		-18.7
Jul	617	0.7
Jun	613	-6.7
AE ∆% Jun-Jul		-31.2
May	657	3.1
Apr	637	-3.8
AE ∆% Apr-May		-4.8
Mar	662	3.9
Feb	637	2.4
AE ∆% Feb-Mar		45.0
Jan	622	-5.3
Dec 2017	657	-7.7
AE ∆% Dec-Jan		-55.4
Nov	712	13.6
Oct	627	-1.7
AE ∆% Oct-Nov		93.9
Sep	638	13.9
Aug	560	-0.9
Jul	565	-8.9
AE ∆% Jul-Sep		11.8
Jun	620	1.1
May	613	4.1
AE ∆% May -Jun		35.9
Apr	589	-6.7
Mar	631	5.7
AE ∆% Mar-Apr		-8.0
Feb	597	2.1
Jan	585	4.3
AE ∆% Jan-Feb		45.8
Dec 2016	561	-1.8
Nov	571	-1.0
AE ∆% Nov-Dec		-15.6
Oct	577	1.8
Sep	567	-2.9
Aug	584	-8.6
AE ∆% Aug-Oct		-33.4
Jul	639	14.5
Jun	558	-0.4
May	560	-1.9
AE ∆% May-Jul		56.7
Apr	571	8.6
Mar	526	2.1
Feb	515	1.2
AE ∆% Feb-Apr		58.5
Jan	509	-6.8
AE ∆% Jan		-57.0
Dec 2015	546	8.3
Nov	504	4.6
Oct	482	5.7
AE ∆% Oct-Dec		105.6
Sep	456	-12.0
Aug	518	2.4
AE ∆% Aug-Sep		-46.5
Jul	506	5.4
Jun	480	-4.4
May	502	0.0
AE ∆% May-Jul		-3.1
Apr	502	4.6
Mar	480	-11.1
Feb	540	4.9
Jan	515	3.6
Dec 2014	497	12.4
AE ∆% Dec-Apr		35.7
Nov	442	-7.1
Oct	476	1.3
Sep	470	3.1
AE ∆% Sep-Nov		-11.4
Aug	456	13.4
Jul	402	-3.8
Jun	418	-7.3
May	451	11.9
Apr	403	-0.5
Mar	405	-3.6
Feb	420	-5.2
Jan	443	2.3
AE ∆% Jan-Aug		8.0
Dec 2013	433	-2.9
Nov	446	0.5
Oct	444	10.2
Sep	403	5.8
Aug	381	1.6
Jul	375	-20.2
Jun	470	9.8
May	428	-2.9
Apr	441	-0.7
AE ∆% Apr-Dec		-3.1
Mar	444	-0.7
Feb	447	0.2
AE ∆% Feb-Mar		-3.0
Jan	446	11.8
Dec 2012	399	1.8
Nov	392	9.5
Oct	358	-7.0
AE ∆% Oct-Jan		55.7
Sep	385	2.7
Aug	375	1.6
Jul	369	2.5
Jun	360	-2.7
May	370	4.5
AE ∆% May-Sep		22.3
Apr	354	0.0
Mar	354	-3.3
Feb	366	9.3
Jan	335	-1.8
AE ∆% Jan-Apr		11.8
Dec 2011	341	4.0
Nov	328	3.8
Oct	316	3.9
Sep	304	1.7
AE ∆% Sep-Dec		48.4
Aug	299	1.0
Jul	296	-1.7
Jun	301	-1.3
May	305	-1.6
AE ∆% May-Aug		-10.3
Apr	310	3.3
Mar	300	11.1
Feb	270	-12.1
Jan	307	-5.8
AE ∆% Jan-Apr		-14.2
Dec 2010	326	13.6

AE: Annual Equivalent

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

There is additional information of the report of new house sales in Table IIB-2. The stock of unsold houses fell from rates of 6 to 8 percent of sales in 2011 to 4 to 5 percent in 2013 and 3.3 percent in Aug 2020. Robbie Whelan and Conor Dougherty, writing on “Builders fuel home sale rise,” on Feb 26, 2013, published in the Wall Street Journal (http://professional.wsj.com/article/SB10001424127887324338604578327982067761860.html), find that inventories of houses have declined as investors acquire distressed houses of higher quality. Median and average house prices oscillate. In Aug 2020, median prices of new houses sold not seasonally adjusted (NSA) decreased 4.6 percent after decreasing 2.9 percent in

Jul 2020. Average prices decreased 0.8 percent in Aug 2020 and decreased 2.2 percent in Jul 2020. Between Dec 2010 and Aug 2020, median prices increased 29.7 percent, with increases of 6.0 percent in Feb 2016, 4.9 percent in Nov 2015, 2.2 percent in Sep 2015, 13.6 percent in Oct 2014, 4.0 percent in Aug 2014, 4.0 percent in May 2014 and 5.2 percent in Mar 2014.  Average prices increased 26.5 percent between Dec 2010 and Aug 2020, with increases of 5.1 percent in Mar 2016, 4.0 percent in Sep 2015, 4.4 percent in Jul 2015 and 18.3 percent in Oct 2014. Between Dec 2010 and Dec 2012, median prices increased 7.1 percent and average prices increased 2.6 percent. Price increases concentrated in 2012 with increase of median prices of 18.2 percent from Dec 2011 to Dec 2012 and of average prices of 13.8 percent. Median prices increased 16.7 percent from Dec 2012 to Dec 2014, with increase of 13.6 percent in Oct 2014, while average prices increased 24.7 percent, with increase of 18.3 percent in Oct 2014. Median prices decreased 1.5 percent from Dec 2014 to Dec 2015 while average prices fell 5.5 percent. Median prices increased 10.1 percent from Dec 2015 to Dec 2016 while average prices increased 8.5 percent. Median prices increased 5.0 percent from Dec 2016 to Dec 2017 while average prices increased 5.3 percent. Median prices decreased 4.0 percent from Dec 2017 to Dec 2018 while average prices decreased 5.2 percent. Median prices decreased 0.1 percent from Dec 2018 to Dec 2019 while average prices decreased 1.1 percent. Median prices decreased 4.3 percent from Aug 2019 to Aug 2020 while average prices decreased 6.0 percent. Robbie Whelan, writing on “New homes hit record as builders cap supply,” on May 24, 2013, published in the Wall Street Journal (http://online.wsj.com/article/SB10001424127887323475304578500973445311276.html?mod=WSJ_economy_LeftTopHighlights), finds that homebuilders are continuing to restrict the number of new homes for sale. Restriction of available new homes for sale increases prices paid by buyers.

Table IIB-2, US, New House Stocks and Median and Average New Homes Sales Price

	Unsold* Stocks in Equiv. Months of Sales SA %	Median New House Sales Price USD NSA	Month ∆%	Average New House Sales Price USD NSA	Month ∆%
Aug 2020	3.3	312,800	-4.6	369,000	-0.8
Jul	3.6	327,800	-2.9	371,900	-2.2
Jun	4.3	337,700	6.5	380,200	3.1
May	5.3	317,100	2.3	368,700	2.3
Apr	6.8	310,100	-5.5	360,300	-4.0
Mar	6.5	328,200	-1.1	375,400	-2.8
Feb	5.5	331,800	0.9	386,200	0.6
Jan	5.0	328,900	-0.2	384,000	1.7
Dec 2019	5.3	329,500	0.5	377,700	-1.7
Nov	5.6	328,000	1.7	384,400	1.1
Oct	5.5	322,400	2.1	380,300	2.2
Sep	5.3	315,700	-3.5	372,100	-5.2
Aug	5.5	327,000	6.1	392,700	5.1
Jul	6.0	308,300	-1.1	373,500	3.2
Jun	5.5	311,800	-0.3	361,900	-4.5
May	6.7	312,700	-7.8	379,100	-1.6
Apr	6.1	339,000	9.1	385,400	3.4
Mar	5.8	310,600	-3.2	372,700	-2.8
Feb	6.1	320,800	5.0	383,600	6.2
Jan	6.5	305,400	-7.4	361,100	-5.4
Dec 2018	7.4	329,700	6.9	381,800	4.0
Nov	6.5	308,500	-6.0	367,100	-7.0
Oct	7.2	328,300	0.0	394,900	2.2
Sep	6.5	328,300	2.1	386,400	1.4
Aug	6.4	321,400	-1.9	380,900	-2.9
Jul	6.1	327,500	5.5	392,300	6.0
Jun	6.1	310,500	-2.0	370,100	-0.7
May	5.5	316,700	0.7	372,600	-3.2
Apr	5.7	314,400	-6.3	385,100	4.3
Mar	5.4	335,400	2.5	369,200	-1.2
Feb	5.6	327,200	-0.7	373,600	-1.1
Jan	5.6	329,600	-4.0	377,800	-6.2
Dec 2017	5.4	343,300	0.0	402,900	3.7
Nov	4.9	343,400	7.5	388,500	-1.4
Oct	5.5	319,500	-3.6	394,000	3.9
Sep	5.3	331,500	5.5	379,300	2.7
Aug	6.0	314,200	-2.7	369,200	-0.9
Jul	5.9	322,900	2.4	372,400	0.5
Jun	5.3	315,200	-2.6	370,600	-2.1
May	5.3	323,600	4.0	378,400	3.4
Apr	5.5	311,100	-3.3	365,800	-4.8
Mar	5.0	321,700	8.0	384,400	3.8
Feb	5.2	298,000	-5.5	370,500	3.6
Jan	5.3	315,200	-3.6	357,700	-6.5
Dec 2016	5.4	327,000	3.8	382,500	5.3
Nov	5.2	315,000	4.0	363,400	3.2
Oct	5.1	302,800	-3.8	352,200	-3.8
Sep	5.2	314,800	5.3	366,100	3.1
Aug	4.9	298,900	0.5	355,100	0.6
Jul	4.5	297,400	-4.4	353,000	-1.3
Jun	5.2	311,200	5.4	357,800	2.3
May	5.2	295,200	-7.3	349,700	-5.3
Apr	5.1	318,300	5.0	369,300	2.9
Mar	5.5	303,200	-0.9	359,000	5.1
Feb	5.6	305,800	6.0	341,700	-5.4
Jan	5.6	288,400	-2.9	361,200	2.5
Dec 2015	5.1	297,100	-5.0	352,500	-5.5
Nov	5.5	312,600	4.9	373,200	1.2
Oct	5.6	298,000	-0.5	368,900	3.3
Sep	5.9	299,500	2.2	357,200	4.0
Aug	5.0	293,000	0.2	343,300	0.6
Jul	5.2	292,300	2.5	341,200	4.4
Jun	5.4	285,100	-0.8	326,900	-2.8
May	5.0	287,500	-2.4	336,200	-1.2
Apr	4.9	294,500	2.8	340,400	-2.5
Mar	5.1	286,600	0.0	349,300	0.9
Feb	4.5	286,600	-1.8	346,300	-0.6
Jan	4.8	292,000	-3.2	348,300	-6.7
Dec 2014	5.1	301,500	1.1	373,200	7.0
Nov	5.7	298,300	0.4	348,900	-7.6
Oct	5.3	297,000	13.6	377,500	18.3
Sep	5.4	261,500	-10.4	319,100	-10.4
Aug	5.4	291,700	4.0	356,200	3.2
Jul	6.2	280,400	-2.3	345,200	2.1
Jun	5.7	287,000	0.5	338,100	4.5
May	5.2	285,600	4.0	323,500	-0.5
Apr	5.7	274,500	-2.8	325,100	-1.9
Mar	5.6	282,300	5.2	331,500	1.7
Feb	5.3	268,400	-0.5	325,900	-3.4
Jan	5.1	269,800	-2.1	337,300	5.0
Dec 2013	5.2	275,500	-0.6	321,200	-4.3
Nov	5.0	277,100	4.8	335,600	0.0
Oct	4.9	264,300	-2.0	335,700	4.4
Sep	5.4	269,800	5.7	321,400	3.4
Aug	5.5	255,300	-2.6	310,800	-5.8
Jul	5.5	262,200	0.9	329,900	7.8
Jun	4.1	259,800	-1.5	306,100	-2.5
May	4.6	263,700	-5.6	314,000	-6.8
Apr	4.4	279,300	8.5	337,000	12.3
Mar	4.2	257,500	-2.9	300,200	-3.9
Feb	4.1	265,100	5.4	312,500	1.8
Jan	4.0	251,500	-2.6	306,900	2.6
Dec 2012	4.5	258,300	5.4	299,200	2.9
Nov	4.6	245,000	-0.9	290,700	1.9
Oct	4.9	247,200	-2.9	285,400	-4.1
Sep	4.5	254,600	0.6	297,700	-2.6
Aug	4.6	253,200	6.7	305,500	8.2
Jul	4.6	237,400	2.1	282,300	3.9
Jun	4.8	232,600	-2.8	271,800	-3.2
May	4.7	239,200	1.2	280,900	-2.4
Apr	4.9	236,400	-1.4	287,900	1.5
Mar	4.9	239,800	0.0	283,600	3.5
Feb	4.8	239,900	8.2	274,000	3.1
Jan	5.3	221,700	1.4	265,700	1.1
Dec 2011	5.3	218,600	2.0	262,900	5.2
Nov	5.7	214,300	-4.7	250,000	-3.2
Oct	6.0	224,800	3.6	258,300	1.1
Sep	6.3	217,000	-1.2	255,400	-1.5
Aug	6.5	219,600	-4.5	259,300	-4.1
Jul	6.7	229,900	-4.3	270,300	-1.0
Jun	6.6	240,200	8.2	273,100	4.0
May	6.6	222,000	-1.2	262,700	-2.3
Apr	6.7	224,700	1.9	268,900	3.1
Mar	7.2	220,500	0.2	260,800	-0.8
Feb	8.1	220,100	-8.3	262,800	-4.7
Jan	7.3	240,100	-0.5	275,700	-5.5
Dec 2010	7.0	241,200	9.8	291,700	3.5

*Percent of new houses for sale relative to houses sold

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

The depressed level of residential construction and new house sales in the US is evident in Table IIB-3 providing new house sales not seasonally adjusted in Jan-Aug of various years. New house sales increased 14.8 percent from Jan-Aug 2019 to Jan-Aug 2020. New house sales increased 21.5 percent from Jan-Aug 2018 to Jan-Aug 2020. New house sales increased 29.4 percent from Jan-Aug 2017 to Jan-Aug 2020. Sales of new houses are higher in Jan-Aug 2020 relative to Jan-Aug 2016 with increase of 38.3 percent. Sales of new houses are higher in Jan-Aug 2020 relative to Jan-Aug 2015 with increase of 53.5 percent. Sales of new houses in Jan-Aug 2020 are substantially lower than in many years between 1996 and 2020 except for the years from 2008 to 2019. There are several other increases of 81.9 percent relative to 2014, 81.3 percent relative to Jan-Aug 2013, 113.4 percent relative to Jan-Aug 2012, 159.3 percent relative to Jan-Aug 2011, 134.6 percent relative to Jan-Aug 2010, and 107.7 percent relative to Jan-Aug 2009. New house sales in Jan-Aug 2020 are 48.5 percent higher than in Jan-Aug 2008. Sales of new houses in Jan-Aug 2020 are lower by 6.1 percent relative to Jan-Aug 2007, 28.3 percent relative to 2006, 40.2 percent relative to 2005 and 35.6 percent relative to 2004. The housing boom peaked in 2005 and 2006 when increases in fed funds rates to 5.25 percent in Jun 2006 from 1.0 percent in Jun 2004 affected subprime mortgages that were programmed for refinancing in two or three years on the expectation that price increases forever would raise home equity. Higher home equity would permit refinancing under feasible mortgages incorporating full payment of principal and interest (Gorton 2009EFM; see other references in http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Sales of new houses in Jan-Jun 2020 relative to the same period in 2003 fell 28.6 percent and 19.1 percent relative to the same period in 2002. Similar percentage declines are also for 2020 relative to years from 2000 to 2004. Sales of new houses in Jan-Aug 2020 decreased 12.2 per cent relative to the same period in 1998. The population of the US was 179.3 million in 1960 and 281.4 million in 2000 (Hobbs and Stoops 2002, 16). Detailed historical census reports are available from the US Census Bureau at (http://www.census.gov/population/www/censusdata/hiscendata.html). The estimate of the US population is 418.8 million in 2015. The US population increased by 133.6 percent from 1960 to 2015.  The final row of Table IIB-3 reveals catastrophic data: sales of new houses in Jan-Aug 2020 of 542 thousand units are lower by 6.6 percent relative to 580 thousand units of houses sold in Jan-Aug 1977, which is fifteenth year when data become available in 1963. The civilian noninstitutional population increased from 122.416 million in 1963 to 259.175 million in 2019, or 111.7 percent (https://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (http://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.” Note: there are two equal total new houses sold in 2015 of 84 (39 in Jan and 45 in Feb) and 84 in 2016 (39 in Jan and 45 in Feb). There are two other equal total new houses sold of 68 in 2013 (32 in Jan and 36 in Feb) and 68 in 2014 (33 in Jan and 35 in 2014).

Table IIB-3, US, Sales of New Houses Not Seasonally Adjusted, Thousands and %

Jan-Aug 2020	542
Jan-Aug 2019	472
∆% Jan-Aug 2020/Jan-Aug 2019	14.8
Jan-Aug 2018	446
∆% Jan-Aug 2020/Jan-Aug 2018	21.5
Jan-Aug 2017	419
∆% Jan-Aug 2020/Jan-Aug 2017	29.4
Jan-Aug 2016	392
∆% Jan-Aug 2020/Jan-Aug 2016	38.3
Jan-Aug 2015	353
∆% Jan-Aug 2020/Jan-Aug 2015	53.5
Jan-Aug 2014	298
∆% Jan-Aug 2020/Jan-Aug 2014	81.9
Jan-Aug 2013	299
∆% Jan-Aug 2020/Jan-Aug 2013	81.3
Jan-Aug 2012	254
∆% Jan-Aug 2020/Jan-Aug 2012	113.4
Jan-Aug 2011	209
∆% Jan-Aug 2020/  Jan-Aug 2011	159.3
Jan-Aug 2010	231
∆% Jan-Aug 2020/  Jan-Aug 2010	134.6
Jan-Aug 2009	261
∆% Jan-Aug 2020/  Jan-Aug 2009	107.7
Jan-Aug 2008	365
∆% Jan-Aug 2020/ Jan-Aug 2008	48.5
Jan-Aug 2007	577
∆% Jan-Aug 2020/Jan-Aug 2007	-6.1
Jan-Aug 2006	756
∆% Jan-Aug 2020/Jan-Aug 2006	-28.3
Jan-Aug 2005	906
∆% Jan-Aug 2020/Jan-Aug 2005	-40.2
Jan-Aug 2004	841
∆% Jan-Aug 2020/ Jan-Aug 2004	-35.6
Jan-Aug 2003	759
∆% Jan-Aug 2020/ Jan-Aug 2003	-28.6
Jan-Aug 2002	670
∆% Jan-Aug 2020/ Jan-Aug 2002	-19.1
Jan-Aug 2001	633
∆% Jan-Aug 2020/Jan-Aug 2001	-15.8
Jan-Aug 2000	608
∆% Jan-Aug 2020/Jan-Aug 2000	-10.9
Jan-Aug 1998	617
∆% Jan-Aug 2020/Jan-Aug 1998	-12.2
Jan-Aug 1977	580
∆% Jan-Aug 2020/Jan-Aug 1977	-6.6

*Computed using unrounded data

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

The revised level of 306 thousand new houses sold in 2011 is the lowest since 560 thousand in 1963 in the 53 years of available data while the level of 368 thousand in 2012 is only higher than 323 thousand in 2010. The level of sales of new houses of 437 thousand in 2014 is the lowest from 1963 to 2009 with exception of 412 thousand in 1982 and 436 thousand in 1981. The population of the US increased 129.4 million from 179.3 million in 1960 to 308.7 million in 2010, or 72.2 percent. The estimate of the US population is 418.8 million in 2015. The US population increased 133.6 percent from 1960 to 2015. The civilian noninstitutional population increased from 122.416 million in 1963 to 259.175 million in 2019, or 111.7 percent (https://www.bls.gov/data/). The Bureau of Labor Statistics (BLS) defines the civilian noninstitutional population (https://www.bls.gov/lau/rdscnp16.htm#cnp): “The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces.”

Table IIB-4, US, New Houses Sold, NSA Thousands

Period	Sold During Period
1963	560
1964	565
1965	575
1966	461
1967	487
1968	490
1969	448
1970	485
1971	656
1972	718
1973	634
1974	519
1975	549
1976	646
1977	819
1978	817
1979	709
1980	545
1981	436
1982	412
1983	623
1984	639
1985	688
1986	750
1987	671
1988	676
1989	650
1990	534
1991	509
1992	610
1993	666
1994	670
1995	667
1996	757
1997	804
1998	886
1999	880
2000	877
2001	908
2002	973
2003	1,086
2004	1,203
2005	1,283
2006	1,051
2007	776
2008	485
2009	375
2010	323
2011	306
2012	368
2013	429
2014	437
2015	501
2016	561
2017	613
2018	617
2019	683

Source: US Census Bureau https://www.census.gov/construction/nrs/index.html

Chart IIB-1 of the US Bureau of the Census shows the sharp decline of sales of new houses in the US. Sales rose temporarily until about mid 2010 but then declined to a lower plateau followed by increase, stability and new oscillating increase. There is decrease in the final segment followed by marginal increase. There is renewed decline and stabilization with recovery in May-Aug 2020.

Chart IIB-1, US, New One-Family Houses Sold in the US, SAAR (Seasonally Adjusted Annual Rate)

Source: US Census Bureau

https://www.census.gov/construction/nrs/img/c25_curr.gif

Between 1991 and 2001, sales of new houses rose 78.4 percent at the average yearly rate of 6.0 percent, as shown in Table IB-5. Between 1995 and 2005 sales of new houses increased 92.4 percent at the yearly rate of 6.8 percent. There are similar rates in all years from 2000 to 2005. The boom in housing construction and sales began in the 1980s and 1990s. The collapse of real estate culminated several decades of housing subsidies and policies to lower mortgage rates and borrowing terms (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009b), 42-8). Sales of new houses sold in 2019 fell 9.8 percent relative to the same period in 1996 and fell 46.8 percent relative to 2005.

Table IIB-5, US, Percentage Change and Average Yearly Rate of Growth of Sales of New One-Family Houses

	∆%	Average Yearly % Rate
1963-2019	22.0	0.4
1991-2001	78.4	6.0
1995-2005	92.4	6.8
2000-2005	46.3	7.9
1996-2019	-9.8	NA
2000-2019	-22.1	NA
2005-2019	-46.8	NA

NA: Not Applicable

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

Chart IIB-2 of the US Bureau of the Census provides the entire monthly sample of new houses sold in the US between Jan 1963 and Aug 2020 without seasonal adjustment. The series is almost stationary until the 1990s. There is sharp upward trend from the early 1990s to 2005-2006 after which new single-family houses sold collapse to levels below those in the beginning of the series with recent increase.

Chart IIB-2, US, New Single-family Houses Sold, NSA, 1963-2020

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.htm

Chart IIB-2A shows NSA sales of new single-family homes in the United States from 2019 to 2020. There is sharp decrease in Mar-Apr 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event followed by vigorous recovery in May-Aug 2020

Chart IIB-2A, US, New Single-family Houses Sold, NSA, 2019-2020

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

The available historical annual data of median and average prices of new houses sold in the US between 1963 and 2019 is in Table IIB-6. On a yearly basis, median and average prices reached a peak in 2007 and then fell substantially. There is recovery in 2012-2018 followed by decline in 2019.

Table IIB-6, US, Median and Average Prices of New Houses Sold, Annual Data

Period	Median	Average
1963	$18,000	$19,300
1964	$18,900	$20,500
1965	$20,000	$21,500
1966	$21,400	$23,300
1967	$22,700	$24,600
1968	$24,700	$26,600
1969	$25,600	$27,900
1970	$23,400	$26,600
1971	$25,200	$28,300
1972	$27,600	$30,500
1973	$32,500	$35,500
1974	$35,900	$38,900
1975	$39,300	$42,600
1976	$44,200	$48,000
1977	$48,800	$54,200
1978	$55,700	$62,500
1979	$62,900	$71,800
1980	$64,600	$76,400
1981	$68,900	$83,000
1982	$69,300	$83,900
1983	$75,300	$89,800
1984	$79,900	$97,600
1985	$84,300	$100,800
1986	$92,000	$111,900
1987	$104,500	$127,200
1988	$112,500	$138,300
1989	$120,000	$148,800
1990	$122,900	$149,800
1991	$120,000	$147,200
1992	$121,500	$144,100
1993	$126,500	$147,700
1994	$130,000	$154,500
1995	$133,900	$158,700
1996	$140,000	$166,400
1997	$146,000	$176,200
1998	$152,500	$181,900
1999	$161,000	$195,600
2000	$169,000	$207,000
2001	$175,200	$213,200
2002	$187,600	$228,700
2003	$195,000	$246,300
2004	$221,000	$274,500
2005	$240,900	$297,000
2006	$246,500	$305,900
2007	$247,900	$313,600
2008	$232,100	$292,600
2009	$216,700	$270,900
2010	$221,800	$272,900
2011	$227,200	$267,900
2012	$245,200	$292,200
2013	$268,900	$324,500
2014	$288,500	$347,700
2015	$294,200	$352,700
2016	$307,800	$360,900
2017	$323,100	$384,900
2018	$326,400	$385,000
2019	$321,500	$383,900

Source: US Census Bureau https://www.census.gov/construction/nrs/index.html

Prices rose sharply between 2000 and 2005 as shown in Table IIB-7. In fact, prices in 2019 are higher than in 2000. Between 2006 and 2019, median prices of new houses sold increased 30.4 percent and average prices increased 25.5 percent. Between 2018 and 2019, median prices decreased 1.5 percent and average prices decreased 0.3 percent.

Table IIB-7, US, Percentage Change of New Houses Median and Average Prices, NSA, ∆%

	Median New  Home Sales Prices ∆%	Average New Home Sales Prices ∆%
∆% 2000 to 2003	15.4	19.0
∆% 2000 to 2005	42.5	43.5
∆% 2000 to 2019	90.2	85.5
∆% 2005 to 2019	33.5	29.3
∆% 2000 to 2006	45.9	47.8
∆% 2006 to 2019	30.4	25.5
∆% 2009 to 2019	48.4	41.7
∆% 2010 to 2019	45.0	40.7
∆% 2011 to 2019	41.5	43.3
∆% 2012 to 2019	31.1	31.4
∆% 2013 to 2019	19.6	18.3
∆% 2014 to 2019	11.4	10.4
∆% 2015 to 2019	9.3	8.8
∆% 2016 to 2019	4.5	6.4
∆% 2017 to 2019	-0.5	-0.3
∆% 2018 to 2019	-1.5	-0.3

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

Chart IIB-3 of the US Census Bureau provides the entire series of new single-family sales median prices from Jan 1963 to Aug 2020. There is long-term sharp upward trend with few declines until the current collapse. Median prices increased sharply during the Great Inflation of the 1960s and 1970s and paused during the savings and loans crisis of the late 1980s and the recession of 1991. Housing subsidies throughout the 1990s caused sharp upward trend of median new house prices that accelerated after the fed funds rate of 1 percent from 2003 to 2004. There was sharp reduction of prices after 2006 with recovery recently above earlier prices.

 

Chart IIB-3, US, Median Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1963-2020

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

Chart IIB-3A of the US Census Bureau provides the entire series of new single-family sales median prices from Jan 2019 to Jul 2020. There is sharp decline of prices in Mar-Apr 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event followed by vigorous recovery in May-Jun 2020 with decline in Jul-Aug 2020.

Chart IIB-3A, US, Median Sales Price of New Single-family Houses Sold, US Dollars, NSA, 2019-2020

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

Chart IIB-4 of the US Census Bureau provides average prices of new houses sold from the mid-1970s to Aug 2020. There is similar behavior as with median prices of new houses sold in Chart IIB-3. The only stress occurred in price pauses during the savings and loans crisis of the late 1980s and the collapse after 2006 with recent recovery, interrupted in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event.

 

Chart IIB-4, US, Average Sales Price of New Single-family Houses Sold, US Dollars, NSA, 1975-2020

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

Chart IIB-4A of the US Census Bureau provides average prices of new houses sold from Jan 2019 to Aug 2020. Prices declined  in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event with vigorous recovery in May-Jun 2020 followed by decline in Jul-Aug 2020.

Chart IIB-4A, US, Average Sales Price of New Single-family Houses Sold, US Dollars, NSA, 2019-2020

Source: US Census Bureau

https://www.census.gov/construction/nrs/index.html

Chart IIB-5 of the Board of Governors of the Federal Reserve System provides the rate for the 30-year conventional mortgage, the yield of the 30-year Treasury bond and the rate of the overnight federal funds rate, monthly, from 1954 to 2016. All rates decline throughout the period from the Great Inflation of the 1970s through the following Great Moderation and until currently. In Apr 1971, the fed funds rate was 4.15 percent and the conventional mortgage rate 7.31 percent. In November 2012, the fed funds rate was 0.16 percent, the yield of the 30-year Treasury 2.80 percent and the conventional mortgage rate 3.35. The final segment shows an increase in the yield of the 30-year Treasury to 3.61 percent in July 2013 with the fed funds rate at 0.09 percent and the conventional mortgage at 4.37 percent. The final data point shows marginal decrease of the conventional mortgage rate to 3.60 percent in May 2016 with the yield of the 30-year Treasury bond at 2.63 percent and overnight rate on fed funds at 0.37 percent. The recent increase in interest rates if sustained could affect the US real estate market. Shayndi Raice and Nick Timiraos, writing on “Banks cut as mortgage boom ends,” on Jan 9, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303754404579310940019239208), analyze the drop in mortgage applications to a 13-year low, as measured by the Mortgage Bankers Association. Nick Timiraos, writing on “Demand for home loans plunges,” on Apr 24, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702304788404579522051733228402?mg=reno64-wsj), analyzes data in Inside Mortgage Finance that mortgage lending of $235 billion in IQ2014 is 58 percent lower than a year earlier and 23 percent below IVQ2013. Mortgage lending collapsed to the lowest level in 14 years. In testimony before the Committee on the Budget of the US Senate on May 8, 2004, Chair Yellen provides analysis of the current economic situation and outlook (http://www.federalreserve.gov/newsevents/testimony/yellen20140507a.htm): “One cautionary note, though, is that readings on housing activity--a sector that has been recovering since 2011--have remained disappointing so far this year and will bear watching.”

 

Chart IIB-5, US, Thirty-year Conventional Mortgage, Thirty-year Treasury Bond and Overnight Federal Funds Rate, Monthly, 1954-2016

Source: Board of Governors of the Federal Reserve System

http://www.federalreserve.gov/releases/H15/default.htm

Chart IIB-5A of the Board of Governors of the Federal Reserve System provides the yield of the 30-year Treasury bond and the rate of the overnight federal funds rate, monthly, from 1977 to 2020. The Board of Governors of the Federal Reserve System discontinued the conventional mortgage rate in its data bank. The final data point is 0.10 percent for the fed funds rate in Aug 2020 and 1.36 percent for the thirty-year Treasury bond resulting from the massive unconventional monetary policy in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. The conventional mortgage rate stood at 2.94 percent in Aug 2020.

Chart IIB-5A, US, Thirty-year Treasury Bond and Overnight Federal Funds Rate, Monthly, 1977-2020

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H15/default.htm

 

Table IIB-8, US, Fed Funds Rate, Thirty Year Treasury Bond and Conventional Mortgage Rate, Monthly, Percent per Year, Dec 2012 to Aug 2020

	Fed Funds Rate	Yield of Thirty Year Constant Maturity	Conventional Mortgage Rate
2012-12	0.16	2.88	3.35
2013-01	0.14	3.08	3.41
2013-02	0.15	3.17	3.53
2013-03	0.14	3.16	3.57
2013-04	0.15	2.93	3.45
2013-05	0.11	3.11	3.54
2013-06	0.09	3.4	4.07
2013-07	0.09	3.61	4.37
2013-08	0.08	3.76	4.46
2013-09	0.08	3.79	4.49
2013-10	0.09	3.68	4.19
2013-11	0.08	3.8	4.26
2013-12	0.09	3.89	4.46
2014-01	0.07	3.77	4.43
2014-02	0.07	3.66	4.3
2014-03	0.08	3.62	4.34
2014-04	0.09	3.52	4.34
2014-05	0.09	3.39	4.19
2014-06	0.1	3.42	4.16
2014-07	0.09	3.33	4.13
2014-08	0.09	3.2	4.12
2014-09	0.09	3.26	4.16
2014-10	0.09	3.04	4.04
2014-11	0.09	3.04	4
2014-12	0.12	2.83	3.86
2015-01	0.11	2.46	3.67
2015-02	0.11	2.57	3.71
2015-03	0.11	2.63	3.77
2015-04	0.12	2.59	3.67
2015-05	0.12	2.96	3.84
2015-06	0.13	3.11	3.98
2015-07	0.13	3.07	4.05
2015-08	0.14	2.86	3.91
2015-09	0.14	2.95	3.89
2015-10	0.12	2.89	3.8
2015-11	0.12	3.03	3.94
2015-12	0.24	2.97	3.96
2016-01	0.34	2.86	3.87
2016-02	0.38	2.62	3.66
2016-03	0.36	2.68	3.69
2016-04	0.37	2.62	3.61
2016-05	0.37	2.63	3.6
2016-06	0.38	2.45	3.57
2016-07	0.39	2.23	3.44
2016-08	0.4	2.26	3.44
2016-09	0.4	2.35	3.46
2016-10	0.4	2.5	3.47
2016-11	0.41	2.86	3.77
2016-12	0.54	3.11	4.2
2017-01	0.65	3.02	4.15
2017-02	0.66	3.03	4.17
2017-03	0.79	3.08	4.2
2017-04	0.9	2.94	4.05
2017-05	0.91	2.96	4.01
2017-06	1.04	2.8	3.9
2017-07	1.15	2.88	3.97
2017-08	1.16	2.8	3.88
2017-09	1.15	2.78	3.81
2017-10	1.15	2.88	3.9
2017-11	1.16	2.8	3.92
2017-12	1.3	2.77	3.95
2018-01	1.41	2.88	4.03
2018-02	1.42	3.13	4.33
2018-03	1.51	3.09	4.44
2018-04	1.69	3.07	4.47
2018-05	1.7	3.13	4.59
2018-06	1.82	3.05	4.57
2018-07	1.91	3.01	4.53
2018-08	1.91	3.04	4.55
2018-09	1.95	3.15	4.63
2018-10	2.19	3.34	4.83
2018-11	2.2	3.36	4.87
2018-12	2.27	3.10	4.64
2019-01	2.40	3.04	4.46
2019-02	2.40	3.02	4.37
2019-03	2.41	2.98	4.27
2019-04	2.42	2.94	4.14
2019-05	2.39	2.82	4.07
2019-06	2.38	2.57	3.80
2019-07	2.40	2.57	3.77
2019-08	2.13	2.12	3.62
2019-09	2.04	2.16	3.61
2019-10	1.83	2.19	3.69
2019-11	1.55	2.28	3.70
2019-12	1.55	2.30	3.72
2020-01	1.55	2.22	3.62
2020-02	1.58	1.97	3.47
2020-03	0.65	1.46	3.45
2020-04	0.05	1.27	3.31
2020-05	0.05	1.38	3.23
2020-06	0.08	1.49	3.16
2020-07	0.09	1.31	3.02
2020-08	0.10	1.36	2.94

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/H15/default.htm

http://www.freddiemac.com/pmms/pmms30.html

IIB2 United States House Prices. The Federal Housing Finance Agency (FHFA), which regulates Fannie Mae and Freddie Mac, provides the FHFA House Price Index (HPI) that “is calculated using home sales price information from Fannie Mae and Freddie Mac-acquired mortgages” (http://fhfa.gov/webfiles/24216/q22012hpi.pdf 1). The Federal Housing Finance Agency (FHFA), which regulates Fannie Mae and Freddie Mac, provides the FHFA House Price Index (HPI) that “is calculated using home sales price information from Fannie Mae and Freddie Mac-acquired mortgages” (http://fhfa.gov/webfiles/24216/q22012hpi.pdf 1). Table IIA2-1 provides the FHFA HPI for purchases only, which shows behavior similar to that of the Case-Shiller index but with lower magnitudes. House prices catapulted from 2000 to 2003, 2005 and 2006. From IVQ2000 to IVQ2006, the index for the US as a whole rose 55.0 percent, with 62.1 percent for New England, 72.0 percent for Middle Atlantic, 71.2 percent for South Atlantic but only by 33.1 percent for East South Central. Prices fell relative to 2014 for the US and all regions from 2006 with exception of increase of 2.6 percent for East South Central. Prices for the US increased 4.9 percent in IVQ2014 relative to IVQ2013 and 12.9 percent from IVQ2012 to IVQ2014. From IVQ2000 to IVQ2014, prices rose for the US and the four regions in Table IIA2-1.

Table IIA2-1, US, FHFA House Price Index Purchases Only NSA ∆%

	United States	New England	Middle Atlantic	South Atlantic	East South Central
IVQ2000 to IVQ2003	24.0	40.6	35.8	25.9	11.0
IVQ2000 to IVQ2005	50.5	65.0	67.6	62.9	25.4
IVQ2000 to IVQ2006	55.0	62.1	72.0	71.2	33.1
IVQ2005 to IVQ2014	-1.5	-8.7	-2.3	-7.4	8.9
IVQ2006 to IVQ2014	-4.4	-7.1	-4.8	-11.9	2.6
IVQ2007 to IVQ2014	-1.9	-5.1	-5.0	-8.6	0.7
IVQ2011 to IVQ2014	18.9	7.3	6.9	19.9	11.8
IVQ2012 to IVQ2014	12.9	6.8	5.7	13.8	8.6
IVQ2013 to IVQ2014	4.9	2.5	2.2	5.1	4.2
IVQ2000 to IVQ2014	48.3 144.27	50.6 138.40	63.7 127.30	50.9 140.28	36.6 146.07

Source: Federal Housing Finance Agency

http://www.fhfa.gov/KeyTopics/Pages/House-Price-Index.aspx

Data of the FHFA HPI for the remaining US regions are in Table IIA2-2. Behavior is not very different from that in Table IIA2-1 with the exception of East North Central. House prices in the Pacific region doubled between 2000 and 2006. Although prices of houses declined sharply from 2005 and 2006 to 2014 with exception of West South Central and West North Central, there was still appreciation relative to 2000.

Table IIA2-2, US, FHFA House Price Index Purchases Only NSA ∆%

	West South Central	West North Central	East North Central	Mountain	Pacific
IVQ2000 to IVQ2003	11.1	18.3	14.7	18.9	44.6
IVQ2000 to IVQ2005	23.9	31.0	23.8	58.0	107.7
IVQ2000 to IVQ2006	31.6	33.7	23.7	68.6	108.7
IVQ2005 to IVQ2014	26.6	4.7	-5.4	-2.6	-14.7
IVQ2006 to IVQ2014	19.1	2.6	-5.4	-8.7	-15.1
IVQ2007 to IVQ2014	15.2	3.2	-2.1	-5.6	-6.0
IVQ2011 to IVQ2014	18.1	13.5	14.2	32.9	37.6
IVQ2012 to IVQ2014	12.1	8.9	11.1	17.9	24.4
IVQ2013 to IVQ2014	5.9	4.0	4.6	5.5	7.3
IVQ2000 to IVQ2014	56.8 145.53	37.1 158.59	17.1 155.13	53.9 172.46	77.1 132.21

Source: Federal Housing Finance Agency

http://www.fhfa.gov/KeyTopics/Pages/House-Price-Index.aspx

Monthly and 12-month percentage changes of the FHFA House Price Index are in Table IIA2-3. Percentage monthly increases of the FHFA index were positive from Apr to Jul 2011 with exception of declines in May and Aug 2011 while 12-month percentage changes improved steadily from around minus 6.0 percent in Mar to May 2011 to minus 4.5 percent in Jun 2011. The house price index increased 0.5 percent in Jan 2019 and increased 5.6 percent in 12 months. House prices increased 0.5 percent in Feb 2019 and increased 5.3 percent in 12 months. The house price index increased 0.2 percent in Mar 2019 and increased 5.2 percent in 12 months. House prices increased 0.6 percent in Apr 2019 and increased 5.4 percent in 12 months. The house price index increased 0.4 percent in May 2019 and increased 5.3 percent in 12 months. House prices increased 0.2 percent in Jun 2019 and increased 5.1 percent in 12 months. The house price index increased 0.4 percent in Jul 2019 and increased 5.2 percent in 12 months. House prices increased 0.3 percent in Aug 2019 and increased 4.9 percent in 12 months. The house price index increased 0.9 percent in Sep 2019 and increased 5.5 percent in 12 months. House prices increased 0.4 percent in Oct 2019 and increased 5.5 percent in 12 months. The house price index increased 0.4 percent in Nov 2019 and increased 5.3 percent in 12 months. House prices increased 0.8 percent in Dec 2019 and increased 5.7 percent in 12 months. The house price index increased 0.5 percent in Jan 2020 and increased 5.8 percent in 12 months. House prices increased 0.8 percent in Feb 2020 and increased 6.1 percent in 12 months. The house price index increased 0.2 percent in Mar 2020 and increased 6.1 percent in 12 months. House prices increased 0.1 percent in May 2020 and increased 5.6 percent in 12 months. The house price index decreased 0.2 percent in May 2020 and increased 5.0 percent in 12 months. House prices increased 1.0 percent in Jun 2020 and increased 5.7 percent in 12 months. The house price index increased 1.0 percent in Jul 2020 and increased 6.4 percent in 12 months.

Table IIA2-3, US, FHFA House Price Index Purchases Only SA. Month and NSA 12-Month ∆%

		Month ∆% SA			12-Month ∆% NSA
7/1/2020		1.0			6.4
6/1/2020		1.0			5.7
5/1/2020		-0.2			5.0
4/1/2020		0.1			5.6
3/1/2020		0.2			6.1
2/1/2020		0.8			6.1
1/1/2020		0.5			5.8
12/1/2019		0.8			5.7
11/1/2019		0.4			5.3
10/1/2019		0.4			5.5
9/1/2019		0.9			5.5
8/1/2019		0.3			4.9
7/1/2019		0.4			5.2
6/1/2019		0.2			5.1
5/1/2019		0.4			5.3
4/1/2019		0.6			5.4
3/1/2019		0.2			5.2
2/1/2019		0.5			5.3
1/1/2019		0.5			5.6
12/1/2018		0.4			5.9
11/1/2018		0.5			5.9
10/1/2018		0.5			6.0
9/1/2018		0.2			6.0
8/1/2018		0.7			6.3
7/1/2018		0.3			6.3
6/1/2018		0.4			6.6
5/1/2018		0.5			6.6
4/1/2018		0.4			6.6
3/1/2018		0.3			7.0
2/1/2018		0.8			7.4
1/1/2018		0.8			7.4
12/1/2017		0.4			6.4
11/1/2017		0.6			6.5
10/1/2017		0.6			6.4
9/1/2017		0.5			6.4
8/1/2017		0.7			6.5
7/1/2017		0.6			6.3
6/1/2017		0.4			6.1
5/1/2017		0.4			6.4
4/1/2017		0.7			6.6
3/1/2017		0.6			6.2
2/1/2017		0.8			6.4
1/1/2017		0.0			5.7
12/1/2016		0.5			6.2
11/1/2016		0.5			6.1
10/1/2016		0.6			6.1
9/1/2016		0.6			6.0
8/1/2016		0.5			6.0
7/1/2016		0.5			5.6
6/1/2016		0.6			5.6
5/1/2016		0.4			5.6
4/1/2016		0.4			5.8
3/1/2016		0.8			5.8
2/1/2016		0.2			5.3
1/1/2016		0.5			6.0
12/1/2015		0.4			5.5
11/1/2015		0.6			5.7
10/1/2015		0.5			5.6
9/1/2015		0.6			5.6
8/1/2015		0.2			5.1
7/1/2015		0.5			5.4
6/1/2015		0.4			5.3
5/1/2015		0.6			5.5
4/1/2015		0.3			5.1
3/1/2015		0.3			5.2
2/1/2015		0.8			5.1
1/1/2015		0.1			4.7
12/1/2014		0.6			5.0
11/1/2014		0.4			4.8
10/1/2014		0.6			4.4
9/1/2014		0.1			4.1
8/1/2014		0.5			4.6
7/1/2014		0.3			4.4
6/1/2014		0.5			4.7
5/1/2014		0.2			4.7
4/1/2014		0.3			5.5
3/1/2014		0.3			5.8
2/1/2014		0.5			6.4
1/1/2014		0.5			6.6
12/1/2013		0.5			6.8
11/1/2013		0.1			6.7
10/1/2013		0.3			7.2
9/1/2013		0.6			7.5
8/1/2013		0.3			7.3
7/1/2013		0.6			7.7
6/1/2013		0.6			7.4
5/1/2013		0.9			7.2
4/1/2013		0.5			7.0
3/1/2013		1.0			7.0
2/1/2013		0.7			6.7
1/1/2013		0.7			6.2
12/1/2012		0.5			5.1
11/1/2012		0.5			4.8
10/1/2012		0.5			4.8
9/1/2012		0.4			3.8
8/1/2012		0.6			4.0
7/1/2012		0.3			3.2
6/1/2012		0.4			3.1
5/1/2012		0.6			3.1
4/1/2012		0.5			2.1
3/1/2012		0.9			1.8
2/1/2012		0.2			-0.2
1/1/2012		-0.3			-1.3
12/1/2011		0.3			-1.5
11/1/2011		0.5			-2.5
10/1/2011		-0.6			-3.3
9/1/2011		0.6			-2.5
8/1/2011		-0.3			-4.0
7/1/2011		0.2			-3.7
6/1/2011		0.4			-4.5
5/1/2011		-0.3			-6.0
4/1/2011		0.2			-5.7
3/1/2011		-1.0			-5.9
2/1/2011		-1.0			-5.2
1/1/2011		-0.5			-4.5
12/1/2010		-0.7			-3.9
12/1/2009		-1.0			-2.0
12/1/2008		-0.3			-10.4
12/1/2007		-0.5			-3.4
12/1/2006		0.1			2.3
12/1/2005		0.6			9.8
12/1/2004		0.9			10.2
12/1/2003		0.8			8.0
12/1/2002		0.7			7.8
12/1/2001		0.6			6.7
12/1/2000		0.6			7.1
12/1/1999		0.5			6.1
12/1/1998		0.4			5.9
12/1/1997		0.3			3.4
12/1/1996		0.3			2.7
12/1/1995		0.4			3.0
12/1/1994		0.0			2.5
12/1/1993		0.5			3.1
12/1/1992		-0.1			2.4

Source: Federal Housing Finance Agency

https://www.fhfa.gov/DataTools

The bottom part of Table IIA2-3 provides 12-month percentage changes of the FHFA house price index since 1992 when data become available for 1991. Table IIA2-4 provides percentage changes and average rates of percent change per year for various periods. Between 1992 and 2019, the FHFA house price index increased 170.1 percent at the yearly average rate of 3.7 percent. In the period 1992-2000, the FHFA house price index increased 39.2 percent at the average yearly rate of 4.2 percent. The average yearly rate of price increase accelerated to 7.5 percent in the period 2000-2003, 8.5 percent in 2000-2005 and 7.4 percent in 2000-2006. At the margin, the average rate jumped to 10.0 percent in 2003-2005 and 7.4 percent in 2003-2006. House prices measured by the FHFA house price index increased 26.2 percent at the average yearly rate of 1.8 percent between 2006 and 2019 and 29.2 percent between 2005 and 2019 at the average yearly rate of 1.8 percent.

Table IIA2-4, US, FHFA House Price Index, Percentage Change and Average Rate of Percentage Change per Year, Selected Dates 1992-2019

Dec	∆%	Average ∆% per Year
1992-2019	170.1	3.7
1992-2000	39.2	4.2
2000-2003	24.2	7.5
2000-2005	50.2	8.5
2003-2005	21.0	10.0
2005-2019	29.2	1.8
2000-2006	53.7	7.4
2003-2006	23.8	7.4
2006-2019	26.2	1.8

Source: Federal Housing Finance Agency

https://www.fhfa.gov/DataTools

 

The explanation of the sharp contraction of household wealth can probably be found in the origins of the financial crisis and global recession. Let V(T) represent the value of the firm’s equity at time T and B stand for the promised debt of the firm to bondholders and assume that corporate management, elected by equity owners, is acting on the interests of equity owners. Robert C. Merton (1974, 453) states:

“On the maturity date T, the firm must either pay the promised payment of B to the debtholders or else the current equity will be valueless. Clearly, if at time T, V(T) > B, the firm should pay the bondholders because the value of equity will be V(T) – B > 0 whereas if they do not, the value of equity would be zero. If V(T) ≤ B, then the firm will not make the payment and default the firm to the bondholders because otherwise the equity holders would have to pay in additional money and the (formal) value of equity prior to such payments would be (V(T)- B) < 0.”

Pelaez and Pelaez (The Global Recession Risk (2007), 208-9) apply this analysis to the US housing market in 2005-2006 concluding:

“The house market [in 2006] is probably operating with low historical levels of individual equity. There is an application of structural models [Duffie and Singleton 2003] to the individual decisions on whether or not to continue paying a mortgage. The costs of sale would include realtor and legal fees. There could be a point where the expected net sale value of the real estate may be just lower than the value of the mortgage. At that point, there would be an incentive to default. The default vulnerability of securitization is unknown.”

There are multiple important determinants of the interest rate: “aggregate wealth, the distribution of wealth among investors, expected rate of return on physical investment, taxes, government policy and inflation” (Ingersoll 1987, 405). Aggregate wealth is a major driver of interest rates (Ibid, 406). Unconventional monetary policy, with zero fed funds rates and flattening of long-term yields by quantitative easing, causes uncontrollable effects on risk taking that can have profound undesirable effects on financial stability. Excessively aggressive and exotic monetary policy is the main culprit and not the inadequacy of financial management and risk controls.

The net worth of the economy depends on interest rates. In theory, “income is generally defined as the amount a consumer unit could consume (or believe that it could) while maintaining its wealth intact” (Friedman 1957, 10). Income, Y, is a flow that is obtained by applying a rate of return, r, to a stock of wealth, W, or Y = rW (Ibid). According to a subsequent restatement: “The basic idea is simply that individuals live for many years and that therefore the appropriate constraint for consumption decisions is the long-run expected yield from wealth r*W. This yield was named permanent income: Y* = r*W” (Darby 1974, 229), where * denotes permanent. The simplified relation of income and wealth can be restated as:

W = Y/r (1)

Equation (1) shows that as r goes to zero, r →0, W grows without bound, W→∞.

Lowering the interest rate near the zero bound in 2003-2004 caused the illusion of permanent increases in wealth or net worth in the balance sheets of borrowers and also of lending institutions, securitized banking and every financial institution and investor in the world. The discipline of calculating risks and returns was seriously impaired. The objective of monetary policy was to encourage borrowing, consumption and investment but the exaggerated stimulus resulted in a financial crisis of major proportions as the securitization that had worked for a long period was shocked with policy-induced excessive risk, imprudent credit, high leverage and low liquidity by the incentive to finance everything overnight at close to zero interest rates, from adjustable rate mortgages (ARMS) to asset-backed commercial paper of structured investment vehicles (SIV).

The consequences of inflating liquidity and net worth of borrowers were a global hunt for yields to protect own investments and money under management from the zero interest rates and unattractive long-term yields of Treasuries and other securities. Monetary policy distorted the calculations of risks and returns by households, business and government by providing central bank cheap money. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9). ARMS were created to lower monthly mortgage payments by benefitting from lower short-dated reference rates. Financial institutions economized in liquidity that was penalized with near zero interest rates. There was no perception of risk because the monetary authority guaranteed a minimum or floor price of all assets by maintaining low interest rates forever or equivalent to writing an illusory put option on wealth. Subprime mortgages were part of the put on wealth by an illusory put on house prices. The housing subsidy of $221 billion per year created the impression of ever increasing house prices. The suspension of auctions of 30-year Treasuries was designed to increase demand for mortgage-backed securities, lowering their yield, which was equivalent to lowering the costs of housing finance and refinancing. Fannie and Freddie purchased or guaranteed $1.6 trillion of nonprime mortgages and worked with leverage of 75:1 under Congress-provided charters and lax oversight. The combination of these policies resulted in high risks because of the put option on wealth by near zero interest rates, excessive leverage because of cheap rates, low liquidity because of the penalty in the form of low interest rates and unsound credit decisions because the put option on wealth by monetary policy created the illusion that nothing could ever go wrong, causing the credit/dollar crisis and global recession (Pelaez and Pelaez, Financial Regulation after the Global Recession, 157-66, Regulation of Banks, and Finance, 217-27, International Financial Architecture, 15-18, The Global Recession Risk, 221-5, Globalization and the State Vol. II, 197-213, Government Intervention in Globalization, 182-4).

There are significant elements of the theory of bank financial fragility of Diamond and Dybvig (1983) and Diamond and Rajan (2000, 2001a, 2001b) that help to explain the financial fragility of banks during the credit/dollar crisis (see also Diamond 2007). The theory of Diamond and Dybvig (1983) as exposed by Diamond (2007) is that banks funding with demand deposits have a mismatch of liquidity (see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 58-66). A run occurs when too many depositors attempt to withdraw cash at the same time. All that is needed is an expectation of failure of the bank. Three important functions of banks are providing evaluation, monitoring and liquidity transformation. Banks invest in human capital to evaluate projects of borrowers in deciding if they merit credit. The evaluation function reduces adverse selection or financing projects with low present value. Banks also provide important monitoring services of following the implementation of projects, avoiding moral hazard that funds be used for, say, real estate speculation instead of the original project of factory construction. The transformation function of banks involves both assets and liabilities of bank balance sheets. Banks convert an illiquid asset or loan for a project with cash flows in the distant future into a liquid liability in the form of demand deposits that can be withdrawn immediately.

In the theory of banking of Diamond and Rajan (2000, 2001a, 2001b), the bank creates liquidity by tying human assets to capital. The collection skills of the relationship banker convert an illiquid project of an entrepreneur into liquid demand deposits that are immediately available for withdrawal. The deposit/capital structure is fragile because of the threat of bank runs. In these days of online banking, the run on Washington Mutual was through withdrawals online. A bank run can be triggered by the decline of the value of bank assets below the value of demand deposits.

Pelaez and Pelaez (Regulation of Banks and Finance 2009b, 60, 64-5) find immediate application of the theories of banking of Diamond, Dybvig and Rajan to the credit/dollar crisis after 2007. It is a credit crisis because the main issue was the deterioration of the credit portfolios of securitized banks as a result of default of subprime mortgages. It is a dollar crisis because of the weakening dollar resulting from relatively low interest rate policies of the US. It caused systemic effects that converted into a global recession not only because of the huge weight of the US economy in the world economy but also because the credit crisis transferred to the UK and Europe. Management skills or human capital of banks are illustrated by the financial engineering of complex products. The increasing importance of human relative to inanimate capital (Rajan and Zingales 2000) is revolutionizing the theory of the firm (Zingales 2000) and corporate governance (Rajan and Zingales 2001). Finance is one of the most important examples of this transformation. Profits were derived from the charter in the original banking institution. Pricing and structuring financial instruments was revolutionized with option pricing formulas developed by Black and Scholes (1973) and Merton (1973, 1974, 1998) that permitted the development of complex products with fair pricing. The successful financial company must attract and retain finance professionals who have invested in human capital, which is a sunk cost to them and not of the institution where they work.

The complex financial products created for securitized banking with high investments in human capital are based on houses, which are as illiquid as the projects of entrepreneurs in the theory of banking. The liquidity fragility of the securitized bank is equivalent to that of the commercial bank in the theory of banking (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65). Banks created off-balance sheet structured investment vehicles (SIV) that issued commercial paper receiving AAA rating because of letters of liquidity guarantee by the banks. The commercial paper was converted into liquidity by its use as collateral in SRPs at the lowest rates and minimal haircuts because of the AAA rating of the guarantor bank. In the theory of banking, default can be triggered when the value of assets is perceived as lower than the value of the deposits. Commercial paper issued by SIVs, securitized mortgages and derivatives all obtained SRP liquidity on the basis of illiquid home mortgage loans at the bottom of the pyramid. The run on the securitized bank had a clear origin (Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 65):

“The increasing default of mortgages resulted in an increase in counterparty risk. Banks were hit by the liquidity demands of their counterparties. The liquidity shock extended to many segments of the financial markets—interbank loans, asset-backed commercial paper (ABCP), high-yield bonds and many others—when counterparties preferred lower returns of highly liquid safe havens, such as Treasury securities, than the risk of having to sell the collateral in SRPs at deep discounts or holding an illiquid asset. The price of an illiquid asset is near zero.”

Gorton and Metrick (2010H, 507) provide a revealing quote to the work in 1908 of Edwin R. A. Seligman, professor of political economy at Columbia University, founding member of the American Economic Association and one of its presidents and successful advocate of progressive income taxation. The intention of the quote is to bring forth the important argument that financial crises are explained in terms of “confidence” but as Professor Seligman states in reference to historical banking crises in the US, the important task is to explain what caused the lack of confidence. It is instructive to repeat the more extended quote of Seligman (1908, xi) on the explanations of banking crises:

“The current explanations may be divided into two categories. Of these the first includes what might be termed the superficial theories. Thus it is commonly stated that the outbreak of a crisis is due to lack of confidence,--as if the lack of confidence was not in itself the very thing which needs to be explained. Of still slighter value is the attempt to associate a crisis with some particular governmental policy, or with some action of a country’s executive. Such puerile interpretations have commonly been confined to countries like the United States, where the political passions of democracy have had the fullest way. Thus the crisis of 1893 was ascribed by the Republicans to the impending Democratic tariff of 1894; and the crisis of 1907 has by some been termed the ‘[Theodore] Roosevelt panic,” utterly oblivious of the fact that from the time of President Jackson, who was held responsible for the troubles of 1837, every successive crisis had had its presidential scapegoat, and has been followed by a political revulsion. Opposed to these popular, but wholly unfounded interpretations, is the second class of explanations, which seek to burrow beneath the surface and to discover the more occult and fundamental causes of the periodicity of crises.”

Scholars ignore superficial explanations in the effort to seek good and truth. The problem of economic analysis of the credit/dollar crisis is the lack of a structural model with which to attempt empirical determination of causes (Gorton and Metrick 2010SB). There would still be doubts even with a well-specified structural model because samples of economic events do not typically permit separating causes and effects. There is also confusion is separating the why of the crisis and how it started and propagated, all of which are extremely important.

In true heritage of the principles of Seligman (1908), Gorton (2009EFM) discovers a prime causal driver of the credit/dollar crisis. The objective of subprime and Alt-A mortgages was to facilitate loans to populations with modest means so that they could acquire a home. These borrowers would not receive credit because of (1) lack of funds for down payments; (2) low credit rating and information; (3) lack of information on income; and (4) errors or lack of other information. Subprime mortgage “engineering” was based on the belief that both lender and borrower could benefit from increases in house prices over the short run. The initial mortgage would be refinanced in two or three years depending on the increase of the price of the house. According to Gorton (2009EFM, 13, 16):

“The outstanding amounts of Subprime and Alt-A [mortgages] combined amounted to about one quarter of the $6 trillion mortgage market in 2004-2007Q1. Over the period 2000-2007, the outstanding amount of agency mortgages doubled, but subprime grew 800%! Issuance in 2005 and 2006 of Subprime and Alt-A mortgages was almost 30% of the mortgage market. Since 2000 the Subprime and Alt-A segments of the market grew at the expense of the Agency (i.e., the government sponsored entities of Fannie Mae and Freddie Mac) share, which fell from almost 80% (by outstanding or issuance) to about half by issuance and 67% by outstanding amount. The lender’s option to rollover the mortgage after an initial period is implicit in the subprime mortgage. The key design features of a subprime mortgage are: (1) it is short term, making refinancing important; (2) there is a step-up mortgage rate that applies at the end of the first period, creating a strong incentive to refinance; and (3) there is a prepayment penalty, creating an incentive not to refinance early.”

The prime objective of successive administrations in the US during the past 20 years and actually since the times of Roosevelt in the 1930s has been to provide “affordable” financing for the “American dream” of home ownership. The US housing finance system is mixed with public, public/private and purely private entities. The Federal Home Loan Bank (FHLB) system was established by Congress in 1932 that also created the Federal Housing Administration in 1934 with the objective of insuring homes against default. In 1938, the government created the Federal National Mortgage Association, or Fannie Mae, to foster a market for FHA-insured mortgages. Government-insured mortgages were transferred from Fannie Mae to the Government National Mortgage Association, or Ginnie Mae, to permit Fannie Mae to become a publicly-owned company. Securitization of mortgages began in 1970 with the government charter to the Federal Home Loan Mortgage Corporation, or Freddie Mac, with the objective of bundling mortgages created by thrift institutions that would be marketed as bonds with guarantees by Freddie Mac (see Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 42-8). In the third quarter of 2008, total mortgages in the US were $12,057 billion of which 43.5 percent, or $5423 billion, were retained or guaranteed by Fannie Mae and Freddie Mac (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 45). In 1990, Fannie Mae and Freddie Mac had a share of only 25.4 percent of total mortgages in the US. Mortgages in the US increased from $6922 billion in 2002 to $12,088 billion in 2007, or by 74.6 percent, while the retained or guaranteed portfolio of Fannie and Freddie rose from $3180 billion in 2002 to $4934 billion in 2007, or by 55.2 percent.

According to Pinto (2008) in testimony to Congress:

“There are approximately 25 million subprime and Alt-A loans outstanding, with an unpaid principal amount of over $4.5 trillion, about half of them held or guaranteed by Fannie and Freddie. Their high risk activities were allowed to operate at 75:1 leverage ratio. While they may deny it, there can be no doubt that Fannie and Freddie now own or guarantee $1.6 trillion in subprime, Alt-A and other default prone loans and securities. This comprises over 1/3 of their risk portfolios and amounts to 34% of all the subprime loans and 60% of all Alt-A loans outstanding. These 10.5 million unsustainable, nonprime loans are experiencing a default rate 8 times the level of the GSEs’ 20 million traditional quality loans. The GSEs will be responsible for a large percentage of an estimated 8.8 million foreclosures expected over the next 4 years, accounting for the failure of about 1 in 6 home mortgages. Fannie and Freddie have subprimed America.”

               In perceptive analysis of growth and macroeconomics in the past six decades, Rajan (2012FA) argues that “the West can’t borrow and spend its way to recovery.” The Keynesian paradigm is not applicable in current conditions. Advanced economies in the West could be divided into those that reformed regulatory structures to encourage productivity and others that retained older structures. In the period from 1950 to 2000, Cobet and Wilson (2002) find that US productivity, measured as output/hour, grew at the average yearly rate of 2.9 percent while Japan grew at 6.3 percent and Germany at 4.7 percent (see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44).  In the period from 1995 to 2000, output/hour grew at the average yearly rate of 4.6 percent in the US but at lower rates of 3.9 percent in Japan and 2.6 percent in the US. Rajan (2012FA) argues that the differential in productivity growth was accomplished by deregulation in the US at the end of the 1970s and during the 1980s. In contrast, Europe did not engage in reform with the exception of Germany in the early 2000s that empowered the German economy with significant productivity advantage. At the same time, technology and globalization increased relative remunerations in highly-skilled, educated workers relative to those without skills for the new economy. It was then politically appealing to improve the fortunes of those left behind by the technological revolution by means of increasing cheap credit. As Rajan (2012FA) argues:

 

“In 1992, Congress passed the Federal Housing Enterprises Financial Safety and Soundness Act, partly to gain more control over Fannie Mae and Freddie Mac, the giant private mortgage agencies, and partly to promote affordable homeownership for low-income groups. Such policies helped money flow to lower-middle-class households and raised their spending—so much so that consumption inequality rose much less than income inequality in the years before the crisis. These policies were also politically popular. Unlike when it came to an expansion in government welfare transfers, few groups opposed expanding credit to the lower-middle class—not the politicians who wanted more growth and happy constituents, not the bankers and brokers who profited from the mortgage fees, not the borrowers who could now buy their dream houses with virtually no money down, and not the laissez-faire bank regulators who thought they could pick up the pieces if the housing market collapsed. The Federal Reserve abetted these shortsighted policies. In 2001, in response to the dot-com bust, the Fed cut short-term interest rates to the bone. Even though the overstretched corporations that were meant to be stimulated were not interested in investing, artificially low interest rates acted as a tremendous subsidy to the parts of the economy that relied on debt, such as housing and finance. This led to an expansion in housing construction (and related services, such as real estate brokerage and mortgage lending), which created jobs, especially for the unskilled. Progressive economists applauded this process, arguing that the housing boom would lift the economy out of the doldrums. But the Fed-supported bubble proved unsustainable. Many construction workers have lost their jobs and are now in deeper trouble than before, having also borrowed to buy unaffordable houses. Bankers obviously deserve a large share of the blame for the crisis. Some of the financial sector’s activities were clearly predatory, if not outright criminal. But the role that the politically induced expansion of credit played cannot be ignored; it is the main reason the usual checks and balances on financial risk taking broke down.”

 

In fact, Raghuram G. Rajan (2005) anticipated low liquidity in financial markets resulting from low interest rates before the financial crisis that caused distortions of risk/return decisions provoking the credit/dollar crisis and global recession from IVQ2007 to IIQ2009. Near zero interest rates of unconventional monetary policy induced excessive risks and low liquidity in financial decisions that were critical as a cause of the credit/dollar crisis after 2007. Rajan (2012FA) argues that it is not feasible to return to the employment and income levels before the credit/dollar crisis because of the bloated construction sector, financial system and government budgets.

Table IIA-2 shows the euphoria of prices during the housing boom and the subsequent decline. House prices rose 64.7 percent in the US national home price index between Jul 2000 and Jul 2005. Prices rose 74.6 percent in the US national index from Jul 2000 to Jul 2006. House prices rose 29.3 percent between Jul 2003 and Jul 2005 for the US national propelled by low fed funds rates of 1.0 percent between Jun 2003 and Jun 2004.  Fed funds rates increased by 0.25 basis points at every meeting of the Federal Open Market Committee (FOMC) from Jul 2004 until Jun 2006, reaching 5.25 percent. Simultaneously, the suspension of auctions of the 30-year Treasury bond caused decrease of yields of mortgage-backed securities with intended increase in mortgage rates. Similarly, between Jul 2003 and Jul 2006 the US national increased 37.1 percent. House prices have increased from Jul 2006 to Jul 2020 by 20.1 percent for the US national. Measuring house prices is quite difficult because of the lack of homogeneity that is typical of standardized commodities. In the 12 months ending in Jul 2020, house prices increased 4.8 percent in the US national. Table IIA-2 also shows that house prices increased 109.6 percent between Jul 2000 and Jul 2020 for the US national. House prices are close to the lowest level since peaks during the boom before the financial crisis and global recession. The US national increased 20.1 percent in Jun 2020 from the peak in Jun 2006 and increased 20.1 percent from the peak in Jul 2006. The final part of Table II-2 provides average annual percentage rates of growth of the house price indexes of Standard & Poor’s Case-Shiller. The average rate for the US national was 3.6 percent from Dec 1987 to Dec 2019 and 3.6 percent from Dec 1987 to Dec 2000. Although the global recession affecting the US between IVQ2007 (Dec) and IIQ2009 (Jun) caused decline of house prices of slightly above 30 percent, the average annual growth rate between Dec 2000 and Dec 2019 was 3.6 percent for the US national.

Table IIA-2, US, Percentage Changes of Standard & Poor’s Case-Shiller National Home Price Indices, Not Seasonally Adjusted, ∆%

	US National
∆% Jul 2000 to Jul 2003	27.4
∆% Jul 2000 to Jul 2005	64.7
∆% Jul 2003 to Jul 2005	29.3
∆% Jul 2000 to Jul 2006	74.6
∆% Jul 2003 to Jul 2006	37.1
∆% Jul 2005 to Jul 2020	27.3
∆% Jul 2006 to Jul 2020	20.1
∆% Jul 2009 to Jul 2020	47.0
∆% Jul 2010 to Jul 2020	50.2
∆% Jul 2011 to Jul 2020	55.7
∆% Jul 2012 to Jul 2020	53.6
∆% Jul 2013 to Jul 2020	40.0
∆% Jul 2014 to Jul 2020	32.6
∆% Jul 2015 to Jul 2020	27.0
∆% Jul 2016 to Jul 2020	21.1
∆% Jul 2017 to Jul 2020	14.5
∆% Jul 2018 to Jul 2020	8.1
∆% Jul 2019 to Jul 2020	4.8
∆% Jul 2000 to Jul 2020	109.6
∆% Peak Jun 2006 to Jul 2020	20.1
∆% Peak Jul 2006 to Jul 2020	20.1
Average ∆% Dec 1987-Dec 2019	3.6
Average ∆% Dec 1987-Dec 2000	3.6
Average ∆% Dec 1992-Dec 2000	4.5
Average ∆% Dec 2000-Dec 2019	3.6

Source: https://my.spindices.com/indices/real-estate/sp-corelogic-case-shiller-us-national-home-price-nsa-index

Monthly house prices increased sharply from Feb 2013 to Jan 2014 for both the SA and NSA national house price, as shown in Table IIA-3. In Jan 2013, the seasonally adjusted national house price index increased 0.9 percent and the NSA increased 0.3. House prices increased at high monthly percentage rates from Feb to Nov 2013. The most important seasonal factor in house prices is school changes for wealthier homeowners with more expensive houses. With seasonal adjustment, house prices fell from Dec 2010 throughout Mar 2011 and then increased in every month from Apr to Jul 2011 but fell in every month from Aug 2011 to Feb 2012. The not seasonally adjusted index registers increase in Mar 2012 of 1.4 percent.  Not seasonally adjusted house prices increased 1.9 percent in Apr 2012 and at high monthly percentage rates through Aug 2012. House prices not seasonally adjusted stalled from Oct 2012 to Dec 2012 and surged from Feb to Sep 2013, decelerating in Oct 2013-Jan 2014. House prices grew at fast rates in Mar-Jul 2014. The SA national house price index increased 0.4 percent in Jul 2020 and the NSA index increased 0.8 percent. Declining house prices cause multiple adverse effects of which two are quite evident. (1) There is a disincentive to buy houses in continuing price declines. (2) More mortgages could be losing fair market value relative to mortgage debt. Another possibility is a wealth effect that consumers restrain purchases because of the decline of their net worth in houses.

Table IIA-2, US, Monthly Percentage Change of S&P Corelogic Case-Shiller National Home Price Indices, Seasonally Adjusted and Not Seasonally Adjusted, ∆%

		SA ∆%			NSA ∆%
December 2010		-0.1			-0.8
January 2011		-0.4			-1.1
February 2011		-0.8			-0.9
March 2011		-0.3			0.0
April 2011		0.0			1.0
May 2011		-0.1			1.1
June 2011		0.0			0.9
July 2011		-0.1			0.3
August 2011		-0.3			-0.4
September 2011		-0.5			-1.1
October 2011		-0.5			-1.3
November 2011		-0.6			-1.3
December 2011		-0.3			-1.1
January 2012		0.0			-0.7
February 2012		-0.1			-0.1
March 2012		1.0			1.4
April 2012		0.9			1.9
May 2012		0.7			1.9
June 2012		0.6			1.5
July 2012		0.4			0.8
August 2012		0.4			0.3
September 2012		0.4			-0.2
October 2012		0.5			-0.3
November 2012		0.7			0.0
December 2012		0.6			-0.1
January 2013		0.9			0.3
February 2013		0.6			0.6
March 2013		1.5			1.9
April 2013		1.0			2.0
May 2013		0.9			1.9
June 2013		0.9			1.7
July 2013		0.9			1.2
August 2013		0.9			0.7
September 2013		0.8			0.2
October 2013		0.6			-0.1
November 2013		0.5			-0.1
December 2013		0.6			-0.1
January 2014		0.6			0.1
February 2014		0.4			0.3
March 2014		0.3			0.8
April 2014		0.2			1.1
May 2014		0.2			1.1
June 2014		0.2			0.9
July 2014		0.2			0.6
August 2014		0.5			0.2
September 2014		0.4			-0.1
October 2014		0.4			-0.2
November 2014		0.4			-0.1
December 2014		0.4			-0.1
January 2015		0.4			-0.1
February 2015		0.3			0.2
March 2015		0.4			0.9
April 2015		0.3			1.1
May 2015		0.3			1.1
June 2015		0.3			0.9
July 2015		0.3			0.6
August 2015		0.6			0.3
September 2015		0.5			0.1
October 2015		0.6			0.0
November 2015		0.5			0.1
December 2015		0.5			0.0
January 2016		0.4			0.0
February 2016		0.2			0.1
March 2016		0.3			0.8
April 2016		0.3			1.1
May 2016		0.4			1.0
June 2016		0.4			0.9
July 2016		0.2			0.6
August 2016		0.7			0.4
September 2016		0.5			0.2
October 2016		0.5			0.0
November 2016		0.5			0.1
December 2016		0.5			0.1
January 2017		0.6			0.1
February 2017		0.3			0.2
March 2017		0.4			0.8
April 2017		0.4			1.1
May 2017		0.4			1.1
June 2017		0.5			0.9
July 2017		0.3			0.7
August 2017		0.8			0.4
September 2017		0.6			0.2
October 2017		0.5			0.1
November 2017		0.6			0.2
December 2017		0.6			0.2
January 2018		0.6			0.1
February 2018		0.5			0.4
March 2018		0.4			0.8
April 2018		0.4			1.0
May 2018		0.4			0.9
June 2018		0.4			0.8
July 2018		0.0			0.4
August 2018		0.6			0.2
September 2018		0.3			0.0
October 2018		0.4			0.0
November 2018		0.2			-0.1
December 2018		0.2			-0.2
January 2019		0.2			-0.2
February 2019		0.2			0.1
March 2019		0.3			0.7
April 2019		0.3			0.9
May 2019		0.3			0.8
June 2019		0.2			0.6
July 2019		0.0			0.4
August 2019		0.6			0.2
September 2019		0.4			0.1
October 2019		0.4			0.0
November 2019		0.4			0.1
December 2019		0.4			0.1
January 2020		0.5			0.0
February 2020		0.5			0.4
March 2020		0.5			0.9
April 2020		0.4			1.0
May 2020		0.1			0.6
June 2020		0.2			0.6
July 2020		0.4			0.8

Source: https://my.spindices.com/indices/real-estate/sp-corelogic-case-shiller-us-national-home-price-nsa-

Table IIA-4 summarizes the brutal drops in assets and net worth of US households and nonprofit organizations from 2007 to 2008 and 2009. Total assets fell $9.1 trillion or 10.7 percent from 2007 to 2008 and $8.1 trillion or 9.5 percent to 2009. Net worth fell $9.0 trillion from 2007 to 2008 or 12.8 percent and $7.9 trillion to 2009 or 11.2 percent. Subsidies to housing prolonged over decades together with interest rates at 1.0 percent from Jun 2003 to Jun 2004 inflated valuations of real estate and risk financial assets such as equities. The increase of fed funds rates by 25 basis points until 5.25 percent in Jun 2006 reversed carry trades through exotic vehicles such as subprime adjustable rate mortgages (ARM) and world financial markets. Short-term zero interest rates encourage financing of everything with short-dated funds, explaining the SIVs created off-balance sheet to issue short-term commercial paper to purchase default-prone mortgages that were financed in overnight or short-dated sale and repurchase agreements (Pelaez and Pelaez, Financial Regulation after the Global Recession, 50-1, Regulation of Banks and Finance, 59-60, Globalization and the State Vol. I, 89-92, Globalization and the State Vol. II, 198-9, Government Intervention in Globalization, 62-3, International Financial Architecture, 144-9).

Table IIA-4, Difference of Balance Sheet of Households and Nonprofit Organizations, Billions of Dollars from 2007 to 2008 and 2009

	2007	2008	Change to 2008	2009	Change to 2009
A	85,162.3	76,039.9	-9,122.4	77,035.2	-8,127.1
Non FIN	30,537.5	27,981.2	-2,556.3	26,010.2	-4,527.3
RE	25,745.9	23,067.0	-2,678.9	21,079.6	-4,666.3
FIN	54,624.8	48,058.7	-6,566.1	51,025.1	-3,599.7
LIAB	14,502.0	14,398.4	-103.6	14,275.9	-226.1
NW	70,660.3	61,641.5	-9,018.8	62,759.3	-7,901.0

Source: Board of Governors of the Federal Reserve System. 2020. Flow of funds, balance sheets and integrated macroeconomic accounts: second quarter 2020. Washington, DC, Federal Reserve System, Jun 21. https://www.federalreserve.gov/releases/z1/current/default.htm

The apparent improvement in Table IIA-4A is mostly because of increases in valuations of risk financial assets by the carry trade from zero interest rates to leveraged exposures in risk financial assets such as stocks, high-yield bonds, emerging markets, commodities and so on. Zero interest rates also act to increase net worth by reducing debt or liabilities. The net worth of households has become an instrument of unconventional monetary policy by zero interest rates in the theory that increases in net worth increase consumption that accounts for 67.1 percent of GDP in IIQ2020 (Section I and earlier) (https://cmpassocregulationblog.blogspot.com/2020/08/d-ollar-devaluation-and-yuan.html), generating demand to increase aggregate economic activity and employment. There are neglected and counterproductive risks in unconventional monetary policy. Between 2007 and IIQ2020, real estate increased in value by $8660.5 billion and financial assets increased $32,391.1 billion for net gain of real estate and financial assets of $39,923.6 billion, explaining most of the increase in net worth of $48,295.0 billion obtained by deducting the increase in liabilities of $1977.8 billion from the increase of assets of $50,273.0 billion (with minor rounding error). Net worth increased from $70,660.3 billion in IVQ2007 to $118,955.3 billion in IIQ2020 by $48,295.0 billion or 68.3 percent. The US consumer price index for all items increased from 210.036 in Dec 2007 to 257.797 in Jun 2020 (https://www.bls.gov/cpi/data.htm) or 22.7 percent. Net worth adjusted by CPI inflation increased 37.2 percent from 2007 to IIQ2020. Real estate assets adjusted for CPI inflation increased 8.9 percent from 2007 to IIQ2020. There are multiple complaints that unconventional monetary policy concentrates income on wealthier individuals because of their holdings of financial assets while the middle class has gained less because of fewer holdings of financial assets and higher share of real estate in family wealth. There is nothing new in these arguments. Interest rate ceilings on deposits and loans have been commonly used. The Banking Act of 1933 imposed prohibition of payment of interest on demand deposits and ceilings on interest rates on time deposits. These measures were justified by arguments that the banking panic of the 1930s was caused by competitive rates on bank deposits that led banks to engage in high-risk loans (Friedman, 1970, 18; see Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 74-5). The objective of policy was to prevent unsound loans in banks. Savings and loan institutions complained of unfair competition from commercial banks that led to continuing controls with the objective of directing savings toward residential construction. Friedman (1970, 15) argues that controls were passive during periods when rates implied on demand deposit were zero or lower and when Regulation Q ceilings on time deposits were above market rates on time deposits. The Great Inflation or stagflation of the 1960s and 1970s changed the relevance of Regulation Q. Friedman (1970, 26-7) predicted the future:

“The banks have been forced into costly structural readjustments, the European banking system has been given an unnecessary competitive advantage, and London has been artificially strengthened as a financial center at the expense of New York.”

In short, Depression regulation exported the US financial system to London and offshore centers. What is vividly relevant currently from this experience is the argument by Friedman (1970, 27) that the controls affected the most people with lower incomes and wealth who were forced into accepting controlled-rates on their savings that were lower than those that would be obtained under freer markets. As Friedman (1970, 27) argues:

“These are the people who have the fewest alternative ways to invest their limited assets and are least sophisticated about the alternatives.” Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. US economic growth has been at only 1.2 percent on average in the cyclical expansion in the 44 quarters from IIIQ2009 to IIQ2020 and in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIQ2020 (https://www.bea.gov/sites/default/files/2020-09/gdp2q20_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.8 percent obtained by dividing GDP of $15,557.3 billion in IIQ2010 by GDP of $15,134.1 billion in IIQ2009 {[($15,557.3/$15,134.1) -1]100 = 2.8%], or accumulating the quarter on quarter growth rates (Section I and earlier) (https://cmpassocregulationblog.blogspot.com/2020/08/d-ollar-devaluation-and-yuan.html). The expansion from IQ1983 to IQ1986 was at the average annual  growth rate of 5.7 percent, 5.3 percent from IQ1983 to IIIQ1986, 5.1 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.6 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991, 3.7 percent from IQ1983 to IVQ1991, 3.7 percent from IQ1983 to IQ1992, 3.7 percent from IQ1983 to IIQ1992, 3.7 percent from IQ1983 to IIIQ2019, 3.8 percent from IQ1983 to IVQ1992, 3.7 percent from IQ1983 to IQ1993, 3.6 percent from IQ1983 to IIQ1993, 3.6 percent from IQ1983 to IIIQ1993, 3.7 percent from IQ1983 to IVQ1993 and at 7.9 percent from IQ1983 to IVQ1983 (Section I and earlier) (https://cmpassocregulationblog.blogspot.com/2020/08/d-ollar-devaluation-and-yuan.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (https://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (https://apps.bea.gov/iTable/index_nipa.cfm). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIQ2020 and in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event would have accumulated to 44.7 percent. GDP in IIQ2020 would be $22,807.6 billion (in constant dollars of 2012) if the US had grown at trend, which is higher by $5505.1 billion than actual $17,302.5 billion. There are more than five trillion dollars of GDP less than at trend, explaining the 34.8 million unemployed or underemployed equivalent to actual unemployment/underemployment of 20.2 percent of the effective labor force with the largest part originating in the global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event (https://cmpassocregulationblog.blogspot.com/2020/09/exchange-rate-fluctuations-1.html and earlier https://cmpassocregulationblog.blogspot.com/2020/08/thirty-eight-million-unemployed-or.html). Unemployment is decreasing while employment is increasing in initial adjustment of the lockdown of economic activity in the global recession resulting from the COVID-19 event (https://www.bls.gov/cps/employment-situation-covid19-faq-june-2020.pdf). US GDP in IIQ2020 is 24.1 percent lower than at trend. US GDP grew from $15,762.0 billion in IVQ2007 in constant dollars to $17,302.5 billion in IIQ2020 or 9.8 percent at the average annual equivalent rate of 0.7 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 2.9 percent per year from Aug 1919 to Aug 2020. Growth at 2.9 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 155.5554 in Aug 2020. The actual index NSA in Aug 2020 is 99.2841 which is 36.2 percent below trend. The underperformance of manufacturing in Mar-Aug 2020 originates partly in the earlier global recession augmented by the current global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19. Manufacturing grew at the average annual rate of 3.3 percent between Dec 1986 and Dec 2006. Growth at 3.3 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 163.3909 in Aug 2020. The actual index NSA in Aug 2020 is 99.2841, which is 39.2 percent below trend. Manufacturing output grew at average 1.7 percent between Dec 1986 and Aug 2020. Using trend growth of 1.7 percent per year, the index would increase to 134.0774 in Aug 2020. The output of manufacturing at 99.2841 in Aug 2020 is 26.0 percent below trend under this alternative calculation. Using the NAICS (North American Industry Classification System), manufacturing output fell from the high of 110.5147 in Jun 2007 to the low of 86.3800 in Apr 2009 or 21.8 percent. The NAICS manufacturing index increased from 86.3800 in Apr 2009 to 100.4257 in Aug 2020 or 16.3 percent. The NAICS manufacturing index increased at the annual equivalent rate of 3.5 percent from Dec 1986 to Dec 2006. Growth at 3.5 percent would increase the NAICS manufacturing output index from 106.6777 in Dec 2007 to 164.9372 in Aug 2020. The NAICS index at 100.4257 in Aug 2020 is 39.1 below trend. The NAICS manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999 to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output index from 106.6777 in Dec 2007 to 132.0705 in Aug 2020. The NAICS index at 100.4257 in Aug 2020 is 24.0 percent below trend under this alternative calculation.

Table IIA-4A, US, Difference of Balance Sheet of Households and Nonprofit Organizations Billions of Dollars from 2007 to 2018, 2019 and IIQ2020

	Value 2007	Change to 2018	Change to 2019	Change to IIQ2020
Assets	85,162.3	36,478.7	49,791.9	50,273.0
Nonfinancial	30,537.5	7,311.8	9,388.8	10,349.3
Real Estate	25,745.9	5,959.1	7,780.8	8,660.5
Financial	54,624.8	29,166.8	40,403.3	39,923.6
Liabilities	14,502.0	1,374.7	1,875.4	1,977.8
Net Worth	70,660.3	35,103.9	47,916.4	48,295.0

Notes: Deposits: Total Time and Savings Deposits FL15303005; Net Worth = Assets – Liabilities

Source: Board of Governors of the Federal Reserve System. 2020. Flow of funds, balance sheets and integrated macroeconomic accounts: second quarter 2020. Washington, DC, Federal Reserve System, Jun 21. https://www.federalreserve.gov/releases/z1/current/default.htm

 

© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.