Currency Substitution and Financial Repression

In this paper, we use a general equilibrium overlapping generations monetary endogenous growth model of a small open economy, to analyze whether financial repression, measured via the “high†mandatory reserve-deposit requirements of financial intermediaries, is an optimal response of a consolidated government following an increase in the degree of currency substitution. We find that higher currency substitution can yield higher reserve requirements, but, the result depends crucially on how the consumer weighs money in the utility function relative to domestic and foreign consumptions, and also the size of the government.

Endogenous Tax Evasion and Reserve Requirements: A Comparative Study in the Context of European Economies

Given that data indicates several countries with same, or nearly same, degree of tax evasion but widely different levels of reserve requirements, this paper analyzes the relationship between the ``optimal" degree of tax evasion and mandatory cash reserve requirements required to be held by banks using a simple overlapping generations framework. Proceeding on the initial premises that the above observation may be a fallout of the possibilities of multiple levels of tax evasion given the reserve requirements and other policy variables, or that the optimal degree of tax evasion may be completely unaffected by the movements in reserve requirements, we find the latter to be true. The model also suggests the following: (i) An economy with a less corrupt structure will have a higher steady-state of value of reported income; (ii) Increases in the penalty rates of evading taxes would induce consumers to report greater fraction of their income, while increases in the income-tax rates would cause them to evade greater fraction of their income, and ; (iii) The model does not vindicate the popular belief in the literature that, countries with lower percentage of reported income tend to have higher reserve requirementsReserve requirements; Tax evasion

Time-varying persistence in US inflation

The persistence property of inflation is an important issue not only for economists, but especially for central banks, given that the degree of inflation persistence determines the extent to which central banks can control inflation. Further, not only is it the level of inflation persistence that is important in economic analyses, but also the question of whether the persistence varies over time, for instance, across business cycle phases, is equally pertinent, since assuming constant persistence across states of the economy is sure to lead to misguided policy decisions. Against this backdrop, we extend the literature on long-memory models of inflation persistence for the US economy over the monthly period of 1920:1\u20132014:5, by developing an autoregressive fractionally integrated moving-average-generalized autoregressive conditional heteroskedastic model with a time-varying memory coefficient which varies across expansions and recessions. In sum, we find that inflation persistence does vary across recessions and expansions, with it being significantly higher in the former than in the latter. As an aside, we also show that persistence of inflation volatility is higher during expansions than in recessions. Understandably, our results have important policy implications

Measuring the welfare cost of inflation in South Africa

In this paper, we estimate the long-run equilibrium relationship between money balance as a ratio of income and the Treasury bill rate for the period of 1965:02 to 2007:01, and, in turn, use the relationship to obtain welfare cost estimates of inflation. Using the Johansen (1991, 1995) technique, we estimate a log-log specification and a semi-log model of the above relationship. Based on the fits of the specifications, we decided to rely more on the welfare cost measure obtained under the log-log money demand model. Our estimates suggest that the welfare cost of inflation for South Africa ranges between 0.34 percent and 0.67 percent of GDP, for a band of 3 to 6 percent of inflation. Thus, it seems that the SARB's current inflation target band of 3-6 percent provides quite a good approximation in terms of welfare.

Costly Tax Enforcement and Financial Repression

Using an overlapping generations production-economy model characterised by financial repression, purposeful government expenditures and tax collection costs, we analyse whether financial repression can be explained by the cost of raising taxes. We show that with public expenditures affecting utility of the agents, modest costs of tax collection tend to result in financial repression being pursued as an optimal policy by the consolidated government. However, when public expenditures are purposeless, the above result only holds for relatively higher costs of tax collection. But, more importantly, costs of tax collection cannot produce a monotonic increase in the reserve requirements. Of critical importance in this regard, are the weights the consumer assigns to the public good in the utility function and the size of the government.

Tax evasion and financial repression: A reconsideration using endogenous growth models

Using two dynamic monetary general equilibrium models characterized by endogenous growth, financial repression and endogenously determined tax evasion, we analyze whether financial repression can be explained by tax evasion. When calibrated to four Southern European economies, we show that higher degrees of tax evasion within a country, resulting from a higher level of corruption and a lower penalty rate, yields higher degrees of financial repression as a social optimum. However, a higher degree of tax evasion, due to a lower tax rate, reduces the severity of the financial restriction. In addition, we find the results to be robust across growth models with or without productive public expenditures. The only difference being that the policy parameters in the former case have higher optimal values.Underground Economy; Tax Evasion; Macroeconomic Policy

A Large Factor Model for Forecasting Macroeconomic Variables in South Africa

This paper uses large Factor Models (FMs) which accommodates a large cross-section of macroeconomic time series for forecasting per capita growth rate, inflation, and the nominal short-term interest rate for the South African economy. The FMs used in this study contains 267 quarterly series observed over the period of 1980Q1-2006Q4. The results, based on the RMSEs of one- to four-quarters-ahead out of sample forecasts over 2001Q1 to 2006Q4, indicate that the FMs tend to outperform alternative models such as an unrestricted VAR, Bayesian VARs (BVARs) and a typical New Keynesian Dynamic Stochastic General Equilibrium (NKDSGE) model in forecasting the three variables under consideration, hence, indicating the blessings of dimensionality.Large Factor Model, VAR, BVAR, NKDSGE Model, Forecast Accuracy

Is a DFM Well Suited for Forecasting Regional House Price Inflation?

This paper uses the Dynamic Factor Model (DFM) framework, which accommodates a large cross-section of macroeconomic time series for forecasting regional house price inflation. As a case study, we use data on house price inflation for five metropolitan areas of South Africa. The DFM used in this study contains 282 quarterly series observed over the period 1980Q1-2006Q4. The results, based on the Mean Absolute Errors of one- to four-quarters-ahead out of sample forecasts over the period of 2001Q1 to 2006Q4, indicate that, in majority of the cases, the DFM outperforms the VARs, both classical and Bayesian, with the latter incorporating both spatial and non-spatial models. Our results, thus, indicate the blessing of dimensionality.Dynamic Factor Model, VAR, BVAR, Forecast Accuracy

Could we have predicted the recent downturn in the South African Housing Market?

This paper develops large-scale Bayesian Vector Autoregressive (BVAR) models, based on 268 quarterly series, for forecasting annualized real house price growth rates for large-, medium and small-middle-segment housing for the South African economy. Given the in-sample period of 1980:01 to 2000:04, the large-scale BVARs, estimated under alternative hyperparameter values specifying the priors, are used to forecast real house price growth rates over a 24-quarter out-of-sample horizon of 2001:01 to 2006:04. The forecast performance of the large-scale BVARs are then compared with classical and Bayesian versions of univariate and multivariate Vector Autoregressive (VAR) models, merely comprising of the real growth rates of the large-, medium and small-middle-segment houses, and a large-scale Dynamic Factor Model (DFM), which comprises of the same 268 variables included in the large-scale BVARs. Based on the one- to four-quarters ahead Root Mean Square Errors (RMSEs) over the out-of-sample horizon, we find the large-scale BVARs to not only outperform all the other alternative models, but to also predict the recent downturn in the real house price growth rates for the three categories of the middle-segment-housing over the period of 2003:01 to 2008:02.Dynamic Factor Model, BVAR, Forecast Accuracy

Time-Varying Risk Aversion and the Profitability of Carry Trades: Evidence from the Cross-Quantilogram

open access articleThis paper examines the predictive power of time-varying risk aversion over payoffs to the carry trade strategy via the cross-quantilogram methodology. Our analysis yields significant evidence of directional predictability from risk aversion to daily carry trade returns tracked by the Deutsche Bank G10 Currency Future Harvest Total Return Index. The predictive power of risk aversion is found to be stronger during periods of moderate to high risk aversion and largely concentrated on extreme fluctuations in carry trade returns. While large crashes in carry trade returns are associated with significant rises in investors’ risk aversion, we also found that booms in carry trade returns can be predicted at high quantiles of risk aversion. The results highlight the predictive role of extreme investor sentiment in currency markets and regime specific patterns in carry trade returns that can be captured via quantile-based predictive models