Figure 7: GDP growth, selected coefficients from models with different block lengths
3 4 5 6 7 8 9 10
Note: We report median coefficients together with 90% confidence sets conditional on inclusion from separate estimations with varying block length between three and ten years.
the coefficients on average reserve requirements and its interaction with crises must be reconciled.
There are at least four possible arguments that link the results. First, credit is measured as shares of GDP. That is, if credit growth picks up after increasing reserve requirements, this indicates that credit increases relative to GDP. Second, the correlation of credit and GDP growth may not be extremely high in normal times, as indicated by the finding that credit cycles may take three to four times as long as business cycles (Drehmann et al., 2012). That is, the pure effect of average reserve requirements on growth does not necessarily need to point in the same direction. Third and with respect to the interaction effect, there may be a timing issue after a crisis. A financial crisis may trigger a credit crunch, which lowers investment and thus leads to a strong drop in real GDP growth. To achieve long-run growth in GDP, capital deepening must take place, which may take some time and some advance credit (Kydland and Prescott, 1982). That is, we could expect credit growth to pick up earlier than GDP growth after a crisis. The development of the interaction term over time, as shown in Figures 5 and 7, points to this possibility: coefficient estimates increase as the block length increases. Fourth, we control for credit variables in the regression on GDP growth. That is, the negative effect of reserve requirements on GDP growth is on top of the effect predicted purely by credit volumes, which all turn out to be more important for GDP growth once reserve requirements and crises are included as control variables. The fact that we find negative growth effects of reserve requirements on economic growth in tranquil times is thus not only related to the credit channel, but also due to other effects that are not explicitly controlled for in the specification.19 Negative growth effects from financial repression due to the distortionary nature of changes in reserve requirements have been often predicted in the theoretical literature (see, for instance Roubini and Sala-i Martin, 1995; Basu, 2001) depending on the complementarity (or lack thereof) of private and publicly provided inputs. Effects of changes in reserve requirements on macroeconomic variables that go beyond changes in investment are also reported by
19If we include an interaction effect mean(rr) with any of the three credit volume measures, we find that the individual effect of mean(rr) on GDP growth and its interaction with credit volumes are negative. This indicates that higher reserve requirements indeed weigh negatively on growth not only via a credit channel. A regression that includes interactions of mean(rr) with all three credit volumes simultaneously is hard to interpret due to high degrees of multicollinearity in the credit volume measures.
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Glocker and Towbin (2015), who find reactions of exchange rates and inflation. This, together with a widening of interest rate spreads (Romer, 1985) may lead to net negative effects on economic activity.
Table 3: Nonlinear effects of reserve requirements
Baseline SD(RR) Difference(RR) RR squared
variable pip mean t-stat pip mean t-stat pip mean t-stat pip mean t-stat
mean(rr) 0.543 -1.266 -1.189 0.478 -1.092 -1.144 0.473 -1.080 -1.146 0.618 1.846 0.549
crisis 0.613 0.297 1.194 0.596 0.286 1.184 0.575 0.277 1.193 0.763 0.467 1.257
mean(rr)#crisis 0.209 0.583 0.773 0.160 0.404 0.570 0.151 0.385 0.582 0.397 -5.675 -1.226
sd(rr) 0.370 -0.624 -0.386
sd(rr)#crisis 0.138 0.526 0.484
maxdiff(rr) 0.359 -0.245 -0.366
maxdiff(rr)#crisis 0.129 0.214 0.463
mean(rr)2 0.740 -9.342 -1.282
mean(rr)2#crisis 0.494 23.526 1.431
Controls YES YES YES YES
Fixed effects YES YES YES YES
Observations 306 306 306 306
Note: Columns report the posterior inclusion probability (pip), unconditional mean (mean) and t-statistic conditional on inclusion (t-stat) of the coefficients.
The database of Federico et al. (2014) not only reports average reserve requirements but also differ-entiates requirements across maturities and/or currencies of regulated deposits. Thus, it allows for us to construct and investigate additional measures of reserve requirements that may shed light on the degree of differentiation embodied in different policy strategies with respect to reserves. During crises, more differentiation should allow policymakers a more targeted response to the crisis, having a positive effect on economic growth. During normal times, increased differentiation could either be positive (due to the same targeting argument), or regulatory complexity could weigh negatively on growth. We look at the standard deviation of requirements across categories, and the difference between maximum and minimum requirements to check these hypotheses.20 We use these variables individually and – as for mean(rr) – interact them with the crisis dummy. The findings on control variables are nearly unaffected, thus we report only variables of interest in Table 3. The differentiation measures have only a minor effect on the results obtained for the parameters of our baseline variables of interest. In addition, we find that inclusion probabilities are very similar to those ofmean(rr)and its interaction with the crisis dummy. Regarding the effects of differentiation (sd(rr), maxdiff(rr)and their interactions with the crisis variable), we can confirm the hypothesis of downsides during normal times and upsides during crisis times. However, posterior inclusion probabilities and t-stats are low, and the positive interaction effect is never strong enough to fully counter the negative effect during normal times.
The fourth set of columns in Table 3 presents the model averaging results for models where the quadratic term of the reserve requirements covariate and its interaction with the crisis dummy are included as part of the pool of explanatory variables, capturing a potential nonlinear effect of average reserve requirements on economic growth. A quadratic relation could imply an “optimal level” of requirements, balancing growth against volatility. Indeed, we find that the posterior inclusion
proba-20These are, admittedly, blunt measures for the degree of regulatory differentiability, as they measure the de facto differentiation, rather than regulatory options.
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Figure 8: Joint effect of crisis and reserve requirements: quadratic specifications
crisis mean(rr)
Note: The surface plot reports the quadratic function implied by the coefficients oncrisis, mean(rr), mean(rr)2 and their interactions. Black dots report actual observations.
bilities of these two variables are high, indicating a more complex nature of the link between economic growth and reserve requirements than that implied by linear models, and its modulation by crisis occurrence. The relationship unveiled by the data, however, does not support a simple hump-shaped link and reveals more complicated conditional correlations between these variables. The estimated partial relationship between crisis and reserve requirements (jointly) and economic growth is pre-sented in Figure 8. It reports the joint effect of individual and interaction terms and displays the actual observations on which our estimates are based. The dominating feature is a strong positive effect on growth for larger values of the crisis variable, consistent with the large positive coefficient in our estimations.21 On a more subtle note, we can see some differences when we vary the amount of reserve requirements. For low levels of the crisis occurrence variable (that is, for tranquil periods), the function is strongly hump-shaped. Moreover, the majority of observations have lower reserve require-ments than the function maximum. That is, higher reserve requirerequire-ments could have had a positive effect on growth. This finding is reassuring for the use of reserve requirements, which should provide a safeguard against crises and large economic fluctuations without affecting growth too negatively.
Apparently, this strategy works for medium levels of reserve requirements. For larger values of the crisis variable, we do not find the same hump-shaped relationship. Instead, the relationship flattens, indicating that reserve requirement levels do not affect the growth path after a long and severe finan-cial crisis. However, we must be careful about overinterpreting the results at high crisis values, as we have very few observations at such levels of the variable.
21Note that we calculate all variables as averages over five-year blocks. Thus, the crisis variable (which is binary on a yearly level) can take on the values{0,0.2,0.4,0.6,0.8,1}in the estimation.
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Last, we account for the fact that many developing economies employed reserve requirements for monetary policy or as capital controls, rather than as macroprudential policy. As argued by Walsh (2012) in his discussion of the contribution by Glocker and Towbin (2012), reserve requirements may weigh more negatively on growth under fixed exchange rates. Higher reserve requirements increase the gap between lending and deposit rates necessary to maintain bank profitability. Thus, they should lead to higher capital outflows and currency devaluation. Under a fixed exchange rate regime (where devaluation is not an option), the central bank needs to increase its interest rate or continuously sell reserves in order to counteract the capital outflows. This interest rate tightening, in turn, has an additional negative effect on growth. We test whether we can confirm this hypothesis even in a setup with a focus on longer horizons and allowing for crises. To do so, we make use of the exchange rate arrangement classification of Ilzetzki et al. (2017). We construct two measures in addition to their coarse and fine classification schemes (where increasing index values are associated with lower degrees of exchange rate control). First, we remove all periods in which Ilzetzki et al. (2017) classify the currency as either free-falling or as a “dual market in which parallel market data are missing” (their two last categories). Second, we construct a simple dummy that is one if the fine index is equal or above the median (eight). In addition to exchange rate arrangements, we also test the interaction with the capital openness index of Chinn and Ito (2008).
Independent of the way we measure exchange rate arrangements, we cannot confirm the theoretical hypothesis.22 In all cases, increasingly fixed exchange rates (i.e., lower index values) together with higher reserve requirements tend to be followed by higher growth, as indicated by the negative coef-ficients on the interaction terms. Somewhat pointing in the opposite direction, larger capital account openness in interaction with higher reserve requirements are also good for growth. We draw from this set of results that both our results and the theoretical prediction should be taken with a grain of salt.
First, the time horizon at which predictions of the theoretical model hold is most likely shorter than in our empirical analysis. Furthermore, the theoretical model does not explicitly account for crises, which may heavily influence our estimation results. There remains a considerable number of systemic banking crises even if we exclude periods where exchange rates were freely falling.
6 Conclusion
This paper investigates the effect of reserve requirements on medium- to long-run credit and GDP growth. Adding to the previous literature on reserve requirements, we employ a large international panel study. Our Bayesian estimation framework, aimed at explicitly assessing model uncertainty and incorporating it to our estimates, provides robust evidence on the importance of reserve requirements for growth, and its effect. In terms of credit growth, previously indicated negative effects of reserve requirements seem to be short-lived. After five years, we instead find a robust positive effect of past requirements on current credit growth. In terms of GDP growth, reserve requirements have on average the expected negative effect of regulation, and although they seem to be somewhat helpful on average in mitigating the effects of a crisis, their effect is not robust to specification uncertainty in the economic growth regressions entertained. A nonlinear estimation suggests that medium levels of
22Table A.5 in the Appendix presents the results.
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reserve requirements may in fact be optimal for medium- to long-run growth.
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Appendix
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Table A.1: Variable sources and description
Variable Name Source Description
crisis Laeven and Valencia (2013) Dummy for systemic banking crisis
reserve requirements Federico et al. (2014) Level of reserve requirements, potentially differenti-ated across currencies and maturities of deposits gdp growth/capita World Bank WDI GDP/capita growth (annual %)
credit by financial sector World Bank WDI Domestic Credit Provided By Financial Sector (%GDP)
bank credit to private sector World Bank WDI Domestic Credit To Private Sector By Banks (%GDP)
credit to private sector World Bank WDI Domestic Credit To Private Sector (%GDP)
gdp/capita IMF World Economic
Out-look Gross Domestic Product Per Capita, Current Prices investment/gdp World Bank WDI Gross Capital Formation (%GDP)
household consumption World Bank WDI Household Final Consumption Expenditure (%GDP) govt. consumption World Bank WDI General government final consumption expenditure
(%GDP)
govt. debt (Abbas et al., 2011) Govt. Debt (%GDP) from the Historical Public Debt Database, updated yearly
inflation, cpi World Bank WDI Inflation, CPI (annual %)
inflation, gdp deflator World Bank WDI Inflation, GDP deflator (annual %)
inflation, gdp deflator World Bank WDI Inflation, GDP deflator (annual %)