Too much of a good thing? Households’ macroeconomic conditions and credit dynamics

Martin Hodula; Simona Malovaná; Jan Frait

doi:10.1515/ger-2021-0033

Article

Too much of a good thing? Households’ macroeconomic conditions and credit dynamics

Martin Hodula , Simona Malovaná and Jan Frait

Published/Copyright: February 18, 2022

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From the journal German Economic Review Volume 23 Issue 4

Abstract

Favorable macroeconomic conditions, accompanied by optimistic consumer confidence, can stimulate and shape households’ expectations in such a way that they gradually extrapolate the view of good times lasting “forever”. As a consequence, households can then be inclined to accept a much higher level of indebtedness – higher than they would be willing to take on if they were to correctly perceive a discontinuation of the positive trend in the future. This paper documents the empirical link between the macroeconomic conditions faced by households, the confidence of households as investors and consumers, and households’ demand for credit on a sample of 21 European countries. The well-known procyclicality of household credit is found to grow stronger when favorable macroeconomic conditions are met with optimistic consumer confidence. While household credit goes hand in hand with the improving economy during an economic upturn, it is found to be sticky on the way down. Estimates show that households tend to extrapolate recent and current macroeconomic trends to the future and over-estimate the persistence of favorable or adverse conditions.

Keywords: consumer confidence; extrapolative expectations; households’ indebtedness; macroeconomic conditions; panel data

JEL Classification: G51; E32; E51; E70

Funding statement: Part of the research behind this paper was funded by the Prague University of Economics and Business institutional research support grant no. IP100040 and Technical University of Ostrava grant no. SP2022/38.

Appendix A Data and filtration

A.1 Hodrick–Prescott filter

The household credit gap and credit-to-GDP gap are estimated using data from the BIS and the Hodrick–Prescott filter with λ = 26 , 000, reflecting the fact that the credit cycle is longer than the business cycle while taking into account the length of the sample and the frequency of the data (Drehmann and Yetman 2018). The maximum time span used is between 1990 Q1 and 2018 Q2; for some countries a shorter period is used based on data availability and quality.

Figure A.1

The Household Credit Gap and Credit-to-GDP Gap for Selected Countries (%). Note: Both gaps (the credit gap and the credit-to-GDP gap) are estimated by filtering household credit and the household credit-to-GDP ratio and then expressed as a percentage of the respective trends.

A.2 Data

Table A.1

Data used to estimate the HOME index.

Block	ID	Description	Source	Units
I	1	Gross domestic product, current prices, annual levels, seasonally adjusted	OECD	National currency, millions
	2	Gross disposable income, households and non-profit institutions serving households, current prices, quarterly levels, seasonally adjusted*	OECD	National currency, millions
	3	Gross savings, households and non-profit institutions serving households, current prices, quarterly levels, seasonally adjusted*	OECD	National currency, millions
II	4	Compensation of employees, households, current prices, quarterly levels, seasonally adjusted	OECD	National currency, millions
II	5	Average registered number of employees, seasonally adjusted	OECD	Thousand persons
III	6	Bank interest rates on consumer loans, households, outstanding amounts	ECB, national statistical office or central bank	% pa
III	7	Bank lending rate on loans for house purchase, households, outstanding amounts	ECB, national statistical office or central bank	% pa
IV	8	Residential property prices, nominal, broadest available (i. e., all types of dwelling)	BIS, ECB	2010=100
IV	9	Share price index	BIS	2010=100
V	10	BIS effective exchange rates, nominal, broad index, quarterly averages	BIS	2010=100
V	11	Terms of trade, calculated as ratio of export prices to import prices, exports/imports of goods and services, seasonally adjusted	OECD	2010=100

Table A.2

Summary statistics.

	Annual growth of household credit (%)		Household credit gap (%)		Household credit-to-GDP gap (%)		ROA (%)		NPL (%)		Capital to assets (%)

	Mean	St. dev.	Mean	St. dev.	Mean	St. dev.	Mean	St. dev.	Mean	St. dev.	Mean	St. dev.
AT	3.9	2.9	−0.2	2.9	0.0	2.1	0.5	0.4	2.7	0.4	6.3	1.2
BE	5.6	3.2	−0.9	3.6	−0.7	3.1	0.4	0.6	2.9	0.8	4.5	1.6
CZ	10.7	9.5	−0.6	8.0	−0.5	7.0	1.4	0.3	6.0	4.7	6.2	0.8
DE	1.0	1.3	0.3	2.3	0.2	2.5	0.1	0.2	3.6	1.0	4.7	0.7
DK	4.9	4.5	−0.9	4.9	−0.6	4.3	0.5	0.4	2.4	1.8	6.1	0.8
EE	13.2	20.4	−1.5	18.3	−1.0	16.1	1.7	2.1	1.7	1.6	10.2	1.6
ES	5.8	9.8	−1.3	9.1	−0.6	5.6	0.5	0.6	3.8	2.9	6.9	0.8
FI	7.6	4.1	−0.8	4.4	−0.5	4.5	0.6	0.3	0.5	0.1	6.4	1.7
FR	5.9	3.0	−0.7	3.7	−0.5	3.2	0.3	0.2	3.9	0.7	5.3	0.9
GR	3.5	11.6	−0.7	11.8	−0.4	7.2	−0.7	2.3	17.2	12.3	7.4	1.8
HU	4.6	13.3	−1.0	14.4	−1.1	14.4	0.9	1.2	7.3	5.4	8.4	0.6
IE	5.3	12.4	−1.6	12.5	−2.1	12.8	−0.1	1.6	9.0	8.9	7.2	3.4
IT	5.8	5.5	−0.5	5.2	−0.1	4.0	0.2	0.8	10.1	4.6	6.1	1.0
LV	14.4	34.6	−2.7	27.2	−2.2	21.8	0.7	1.6	5.1	4.9	9.0	1.2
NL	4.3	3.7	−0.2	2.5	−0.1	2.4	0.6	0.7	2.3	0.6	4.5	0.9
PL	14.5	13.3	−1.3	8.7	−0.9	9.6	0.8	1.3	8.9	6.1	8.3	0.6
PT	3.9	6.5	−0.5	5.2	−0.3	3.8	−0.1	1.3	5.5	4.0	6.5	0.9
SE	7.7	2.0	−0.4	2.2	0.0	2.3	0.7	0.2	1.0	0.4	5.0	0.6
SK	17.6	12.1	0.4	4.0	−0.2	4.4	1.0	0.3	5.4	2.8	9.6	1.8
SL	8.0	9.4	−0.8	9.3	−0.5	7.4	–	–	–	–	–	–
UK	5.8	4.6	−0.3	5.3	0.2	3.9	0.5	0.5	2.3	1.1	6.4	1.5


Total	7.0	11.6	−0.7	9.4	−0.5	8.0	0.5	1.2	5.1	5.9	6.8	2.1

Figure A.2

The HOME Index for Advanced Economies and Emerging Market Economies. Note: The index is standardized using its long-run mean and standard deviation; the vertical axis shows the standard deviations. For more details on the HOME index, see Hodula et al. (2021).

Appendix B Additional regression results

B.1 Mean regression analysis

Table B.1

Mean regression – effect of an increase in the HOME index on credit variables when considering additional control variables.

	Dependent variable ( Y t ):

	Annual growth of household credit			Household credit gap			Household credit-to-GDP gap

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
Y t − 1	0.891***	0.882***	0.888***	0.966***	0.979***	0.977***	0.957***	0.962***	0.947***
	(0.008)	(0.008)	(0.008)	(0.006)	(0.006)	(0.006)	(0.008)	(0.009)	(0.009)
HOME t − 1	0.515***			0.462***			−0.107*
	(0.061)			(0.047)			(0.055)
HOME t − 1 (AE)		0.369***			0.345***			−0.129**
		(0.062)			(0.048)			(0.057)
HOME t − 1 (EME)		1.451***			1.253***			0.075
		(0.138)			(0.110)			(0.143)
HOME t − 1 (AE) > 0			0.274**			0.300***			−0.021
			(0.136)			(0.106)			(0.125)
HOME t − 1 (AE) < 0			0.435***			0.348***			−0.298***
			(0.100)			(0.079)			(0.093)
HOME t − 1 (EME) > 0			1.072***			1.516***			1.025***
			(0.258)			(0.176)			(0.209)
HOME t − 1 (EME) < 0			1.720***			0.991***			−0.984***
			(0.209)			(0.174)			(0.222)
ROA t − 1	0.081	−0.022	−0.053	0.257***	0.167***	0.179***	0.170***	0.158***	0.200***
	(0.062)	(0.062)	(0.064)	(0.048)	(0.048)	(0.048)	(0.057)	(0.058)	(0.057)
NPL t − 1	−0.029*	−0.045***	−0.041**	−0.085***	−0.090***	−0.092***	−0.102***	−0.105***	−0.101***
	(0.016)	(0.016)	(0.017)	(0.012)	(0.012)	(0.012)	(0.014)	(0.014)	(0.014)
CA t − 1	−0.014	0.024	0.015	−0.116***	−0.056	−0.039	−0.154***	−0.137***	−0.099**
	(0.048)	(0.047)	(0.048)	(0.037)	(0.037)	(0.037)	(0.044)	(0.045)	(0.045)
Country FE	Y	Y	Y	Y	Y	Y	Y	Y	Y
Time FE	N	N	N	N	N	N	N	N	N
Observations	1,097	1,097	1,097	1,108	1,108	1,108	1,108	1,108	1,108
Adjusted R 2	0.959	0.961	0.961	0.968	0.970	0.970	0.948	0.948	0.950

Note: This table presents estimates based on dynamic panel data regression with country fixed effects. Standard errors are reported in parentheses. ***, **, and * denote the 1 %, 5 %, and 10 % significance levels.

Table B.2

Mean regression – effect of an increase in the HOME index on credit variables when considering time-fixed effects.

	Dependent variable ( Y t ):

	Annual growth of household credit			Household credit gap			Household credit-to-GDP gap

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
Y t − 1	0.883***	0.868***	0.870***	0.947***	0.967***	0.968***	0.958***	0.970***	0.962***
	(0.010)	(0.010)	(0.010)	(0.007)	(0.008)	(0.008)	(0.009)	(0.011)	(0.011)
HOME t − 1	0.371***			0.233***			−0.017
	(0.077)			(0.058)			(0.069)
HOME t − 1 (AE)		0.235***			0.172***			−0.041
		(0.076)			(0.058)			(0.070)
HOME t − 1 (EME)		1.519***			0.905***			0.270*
		(0.146)			(0.122)			(0.156)
HOME t − 1 (AE) > 0			0.146			0.019			−0.075
			(0.142)			(0.111)			(0.132)
HOME t − 1 (AE) < 0			0.314***			0.295***			−0.083
			(0.119)			(0.092)			(0.109)
HOME t − 1 (EME) > 0			1.316***			0.780***			0.820***
			(0.256)			(0.187)			(0.224)
HOME t − 1 (EME) < 0			1.692***			1.041***			−0.343
			(0.223)			(0.187)			(0.239)
ROA t − 1	0.042	−0.085	−0.105*	0.173***	0.105**	0.087*	0.098*	0.084	0.119**
	(0.061)	(0.060)	(0.063)	(0.046)	(0.046)	(0.048)	(0.056)	(0.056)	(0.058)
NPL t − 1	−0.033**	−0.048***	−0.046***	−0.065***	−0.070***	−0.071***	−0.067***	−0.073***	−0.078***
	(0.016)	(0.016)	(0.016)	(0.012)	(0.012)	(0.012)	(0.014)	(0.014)	(0.015)
CA t − 1	0.0001	0.060	0.059	−0.060	−0.011	−0.004	−0.129***	−0.105**	−0.083*
	(0.051)	(0.050)	(0.051)	(0.039)	(0.039)	(0.040)	(0.046)	(0.047)	(0.048)
Country FE	Y	Y	Y	Y	Y	Y	Y	Y	Y
Time FE	Y	Y	Y	Y	Y	Y	Y	Y	Y
Observations	1,097	1,097	1,097	1,108	1,108	1,108	1,108	1,108	1,108
Adjusted R 2	0.903	0.910	0.910	0.947	0.948	0.948	0.924	0.925	0.925

Note: This table presents estimates based on dynamic panel data regression with country and time fixed effects. Standard errors are reported in parentheses. ***, **, and * denote the 1 %, 5 %, and 10 % significance levels.

Table B.3

Mean regression – interaction effects with the CCI dummy variable (2).

	Dependent variable ( Y t ):

	Annual growth of household credit		Household credit gap		Household credit-to-GDP gap

	(1)	(2)	(3)	(4)	(5)	(6)
Y t − 1	0.892***	0.887***	0.966***	0.979***	0.955***	0.951***
	(0.008)	(0.008)	(0.006)	(0.006)	(0.009)	(0.010)
HOME t − 1 (both HOME & CCI > 0)	0.446***		0.568***		0.193*
	(0.123)		(0.092)		(0.107)
HOME t − 1 (HOME & CCI different)	0.051		0.206		−0.082
	(0.166)		(0.131)		(0.152)
HOME t − 1 (both HOME & CCI < 0)	0.660***		0.440***		−0.344***
	(0.093)		(0.076)		(0.089)
HOME t − 1 (AE) (both HOME & CCI > 0)		0.331**		0.345***		−0.040
		(0.132)		(0.103)		(0.121)
HOME t − 1 (AE) (HOME & CCI different)		0.004		0.116		−0.180
		(0.168)		(0.132)		(0.157)
HOME t − 1 (AE) (both HOME & CCI < 0)		0.480***		0.373***		−0.269***
		(0.096)		(0.076)		(0.090)
HOME t − 1 (EME) (both HOME & CCI > 0)		1.196***		1.486***		0.838***
		(0.249)		(0.176)		(0.211)
HOME t − 1 (EME) (HOME & CCI different)		0.700		1.322***		1.029*
		(0.601)		(0.471)		(0.557)
HOME t − 1 (EME) (both HOME & CCI < 0)		1.694***		1.075***		−0.829***
		(0.200)		(0.170)		(0.217)
ROA t − 1	0.059	−0.050	0.260***	0.172 ∗ ∗ ∗	0.192***	0.192***
	(0.063)	(0.064)	(0.048)	(0.048)	(0.058)	(0.058)
NPL t − 1	−0.029*	−0.041**	− 0.082 ∗ ∗ ∗	− 0.089 ∗ ∗ ∗	−0.094***	−0.100***
	(0.016)	(0.017)	(0.012)	(0.012)	(0.014)	(0.014)
CA t − 1	−0.026	0.007	−0.121***	−0.044	−0.149***	−0.102**
	(0.048)	(0.048)	(0.037)	(0.038)	(0.044)	(0.047)
Country FE	Y	Y	Y	Y	Y	Y
Time FE	N	N	N	N	N	N
Observations	1,097	1,097	1,108	1,108	1,108	1,108
Adjusted R 2	0.959	0.961	0.965	0.967	0.946	0.947

Note: This table presents estimates based on dynamic panel data regression with country fixed effects. Standard errors are reported in parentheses. ***, **, and * denote the 1 %, 5 %, and 10 % significance levels.

B.2 Quantile regression analysis

Figure B.1

Quantile Regression – Effect of an Increase in the HOME Index on Credit Variables (2). Note: X-axis – quantiles, y-axis – coefficient size; 90 % confidence intervals reported. The full regression results are given in Appendix B.2, Tables B.3 and B.4. Specifications without supply-side control variables.

Table B.4

Quantile regression – effect of an increase in the HOME index on household credit variables (1).

	Dependent variable ( Y t ):

	Annual growth of household credit				Household credit gap				Household credit-to-GDP gap

	Q 0.20	Q 0.40	Q 0.60	Q 0.80	Q 0.20	Q 0.40	Q 0.60	Q 0.80	Q 0.20	Q 0.40	Q 0.60	Q 0.80

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)
Intercept	−0.245**	0.115**	0.371***	0.729***	−0.573***	−0.239***	0.117*	0.61***	−1.001***	−0.497***	−0.187***	0.281***
	(0.095)	(0.047)	(0.061)	(0.118)	(0.116)	(0.064)	(0.066)	(0.12)	(0.17)	(0.074)	(0.071)	(0.09)
Y t − 1	0.893***	0.943***	0.965***	0.993***	0.945***	0.961***	0.969***	0.981***	0.917***	0.939***	0.941***	0.953***
	(0.018)	(0.012)	(0.01)	(0.016)	(0.012)	(0.008)	(0.008)	(0.014)	(0.017)	(0.01)	(0.008)	(0.012)
HOME t − 1 > 0	0.323**	0.114	−0.017	−0.068	0.417***	0.526***	0.583***	0.821***	0.288*	0.305**	0.41***	0.732***
	(0.133)	(0.07)	(0.081)	(0.125)	(0.115)	(0.112)	(0.175)	(0.317)	(0.147)	(0.118)	(0.125)	(0.208)
HOME t − 1 < 0	0.529***	0.361***	0.352***	0.3***	0.349***	0.251***	0.268***	0.353***	−0.381***	−0.366***	−0.443***	−0.48***
	(0.174)	(0.073)	(0.075)	(0.074)	(0.083)	(0.078)	(0.086)	(0.11)	(0.14)	(0.072)	(0.099)	(0.176)

Note: This table presents estimates based on dynamic panel data quantile regression with country fixed effects. Standard errors are reported in parentheses. ***, **, and * denote the 1 %, 5 %, and 10 % significance levels.

Table B.5

Quantile regression – effect of an increase in the HOME index on household credit variables (2).

	Dependent variable ( Y t ):

	Annual growth of household credit				Household credit gap				Household credit-to-GDP gap

	Q 0.20	Q 0.40	Q 0.60	Q 0.80	Q 0.20	Q 0.40	Q 0.60	Q 0.80	Q 0.20	Q 0.40	Q 0.60	Q 0.80

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)
Intercept	−0.317***	0.035	0.27***	0.589***	−0.516***	−0.133***	0.226***	0.802***	−0.717***	−0.249***	0.152***	0.787***
	(0.107)	(0.061)	(0.057)	(0.122)	(0.061)	(0.025)	(0.032)	(0.106)	(0.069)	(0.021)	(0.034)	(0.109)
Y t − 1	0.881***	0.93***	0.957***	0.989***	0.962***	0.976***	0.981***	0.997***	0.938***	0.953***	0.959***	0.975***
	(0.017)	(0.015)	(0.012)	(0.015)	(0.008)	(0.008)	(0.01)	(0.013)	(0.011)	(0.006)	(0.008)	(0.012)
HOME t − 1 (AE)	0.311***	0.213***	0.158***	0.122	0.336***	0.332***	0.336***	0.458***	−0.107	−0.056	−0.066	−0.044
	(0.056)	(0.043)	(0.046)	(0.079)	(0.051)	(0.05)	(0.06)	(0.094)	(0.076)	(0.063)	(0.057)	(0.077)
HOME t − 1 (EME)	1.451***	1.041***	0.704***	0.563***	1.007***	1.018***	1.072***	1.239***	0.609***	0.636***	0.528**	0.647*
	(0.236)	(0.269)	(0.253)	(0.2)	(0.104)	(0.193)	(0.227)	(0.249)	(0.15)	(0.198)	(0.266)	(0.354)

Note: This table presents estimates based on dynamic panel data quantile regression with country fixed effects. Standard errors are reported in parentheses. ***, **, and * denote the 1 %, 5 %, and 10 % significance levels.

Appendix C Out-of-sample forecasting exercise

In this section, we conduct an out-of-sample direct multi-step forecasting exercise using a recursive window approach. First, we estimate model parameters using selected training sample. Then, we use the estimated parameters to predict the credit variable Y i , t + h (annual credit growth, credit gap or credit-to-GDP gap). Finally, we add an additional data point at the end of the sample and re-estimate the model. We generate h period-ahead forecast at each step and at every horizon from a different model:

(C.1) Y i , t + h = β 1 Y i , t − 1 + β 2 HOME i , t − 1 + v i + μ t + ε i , t

We compare the forecasting accuracy of the baseline model including the HOME index (Eq. (C.1)) with the same specification excluding the HOME index:

(C.2) Y i , t + h = β 1 Y i , t − 1 + v i + μ t + ε i , t

We start with a training period ending in 2010 Q4 (36 quarters) while we sequentially increase the sample at each step, i. e. when a new h period-ahead forecast is calculated. We set the forecasting horizon from 1 to 8 quarters.

To assess the forecasting performance, we compute the root-mean-square error (RMSE) of each model as follows:

(C.3) RMSE h = 1 T 1 I ∑ i = 1 I ∑ t = 1 T Y ˆ i , t + h − Y i , t + h 2

where Y ˆ i , t + h denotes the h-step ahead forecast for time t and country i, Y i , t + h denotes actual realization, T is the total number of computed forecasts, and I is the total number of countries.

To assess the predictive performance of individual models, we compare their RMSE. We report the ratio of RMSE of the baseline model with HOME index against the RMSE of the model without the index. If the RMSE ratio is below one, the baseline model outperforms the model without HOME index. We calculate the ratio of RMSEs across all countries (Total), countries with the credit variable in the first quartile (q25), between the first and fourth quartile (q25–q75) and in the fourth quartile, respectively. In addition, we test for the equal forecasting accuracy of the two models using the Diebold–Mariano statistical test. Specifically, the null hypothesis is that the two models have the same forecast accuracy. Results are reported in Table C.1. As a robustness check, we also use supply-side bank-specific control variables (see Section 4) which yields quantitatively similar results (available upon request).

Table C.1

The ratio of RMSEs over the forecasting horizons.

	Horizon	Total	q25	q25–q75	q75
Annual growth of household credit	1	1.05	1.04	1.20	0.99
	2	1.06	1.05	1.21	0.99
	4	1.05	1.06	1.12	1.00
	6	1.03	1.05	1.06	1.01
	8	1.03	1.04	1.05	1.01
Household credit gap	1	0.85	0.85	0.78	0.90
	2	0.83	0.83	0.77	0.87
	4	0.83	0.84	0.80	0.85
	6	0.86	0.89	0.83	0.85
	8	0.89	0.94	0.87	0.88
Household credit-to-GDP gap	1	0.99	0.99	0.98	1.01
	2	0.99	0.99	0.97	1.01
	4	0.99	0.99	0.98	1.02
	6	0.99	0.99	0.98	1.01
	8	0.99	0.99	0.99	1.01

Note: This table reports the ratio of the RMSE of the baseline model with HOME index (Eq. (C.1)) against the RMSE of the model without HOME index (Eq. (C.2)). If the RMSE ratio is below one, the baseline model with HOME index outperforms the model without HOME index. Columns q25, q25–q75 and q75 report the ratio of RMSEs for countries with the credit variable in the first quartile, between the first and fourth quartile and in the fourth quartile, respectively. Bold (italic) indicates a statistically significant difference in forecasting performance at the 95 % (90 %) level according to the Diebold–Mariano test.

Availability of data and material: The underlying code, data, the resulting index are available for download at the Czech National Bank webpage: https://www.cnb.cz/cs/ekonomicky-vyzkum/publikace-vyzkumu/cnb-working-paper-series/Introducing-a-New-Index-of-Households-Macroeconomic-Conditions/.
Conflict of interest: All authors are employed by the Czech National Bank.

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Published Online: 2022-02-18

Published in Print: 2022-12-31

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Articles in the same Issue

https://doi.org/10.1515/ger-2021-0033

Keywords for this article

consumer confidence; extrapolative expectations; households’ indebtedness; macroeconomic conditions; panel data