WenShwo Fang

Export Promotion through Exchange Rate Policy: Exchange Rate Depreciation or Stabilization?

Exchange rate movements affect exports in two ways -- its depreciation and its variability (risk). A depreciation raises exports, but the associated exchange rate risk could offset that positive effect. The present paper investigates the net effect for eight Asian countries using a dynamic conditional correlation bivariate GARCH-M model that simultaneously estimates time varying correlation and exchange rate risk. Depreciation encourages exports, as expected, for most countries, but its contribution to export growth is weak. Exchange rate risk contributes to export growth in Malaysia and the Philippines, leading to positive net effects. Exchange rate risk generates a negative effect for six of the countries, resulting in a negative net effect in Indonesia, Japan, Singapore, Taiwan and a zero net effect in Korea and Thailand. Since the negative effect of exchange rate risk may offset, or even dominate, positive contributions from depreciation, policy makers need to reduce exchange rate fluctuation along with and possibly before efforts to depreciate the currency.

Exchange rate depreciation and exports: the case of Singapore revisited

This article revisits the weak relationship between exchange rate depreciation and exports for Singapore, using a bivariate generalized autoregressive conditional heteroscedasticity in mean model that simultaneously estimates time-varying risk. The evidence shows that depreciation does not significantly improve exports, but that exchange rate risk significantly impedes exports. In sum, Singaporean policy makers can better promote export growth by stabilizing the exchange rate rather than generating its depreciation.

Cross-Country Evidence on Output Growth Volatility: Nonstationary Variance and Garch Models

This paper revisits the issue of conditional volatility in real gross domestic product (GDP) growth rates for Canada, Germany, Italy, Japan, the United Kingdom, and the United States. Previous studies find high persistence in the volatility. This paper shows that this finding largely reflects a nonstationary variance. Output growth in the six countries became noticeably less volatile over the past few decades. In this paper, we employ the modified iterated cumulative sum of squares (ICSS) algorithm to detect structural change in the variance of output growth. One structural break exists in each of the six countries after identifying outliers and mean shifts in the growth rates. We then use generalized autoregressive conditional heteroskedasticity (GARCH) specifications, modeling output growth and its volatility with and without the break in volatility. The evidence shows that the time-varying variance falls sharply in Canada and Japan, and disappears entirely in Germany, Italy, the United Kingdom and the United States, once we incorporate the break in the variance equation of output for the six countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary variance. Moreover, we also consider the possible effects of our more correct measure of output volatility on output growth as well as the reverse effect of output growth on its volatility. The conditional standard deviation possesses no statistical significance in all countries, except a significant negative effect in Japan. The lagged growth rate of output produces significant negative and positive effects on the conditional variances in Germany and Japan, respectively. No significant effects exist in Canada, Italy, the United Kingdom, and the United States.

The Effect of Growth Volatility on Income Inequality

This paper assesses the long-run effect of growth volatility on income inequality using a comprehensive panel of annual U.S. state-level data during the 1945 to 2004 period. Using the pooled mean group (PMG) estimator, we find overwhelming evidence supporting the hypothesis that larger growth volatility positively and significantly associates with higher income inequality. In addition, our key finding is robust to alternative lag structures, conditioning variables, inequality measures, volatility indicators, and time periods.

Does financial development volatility affect industrial growth volatility

This paper investigates whether volatility of financial development plays a role in determining industrial growth volatility. Three key findings emerge. First, overwhelming evidence supports the view that more volatile financial development raises the industrial volatility in sectors that rely more on external liquidity. Second, the harmful effect of financial volatility on industrial volatility mainly works through the increase in fluctuations of the growth of real value added per firm and the number of firms, with the former effect more prominent. Third, both the volatilities of the banking sector and the stock market positively associate with higher industrial growth volatility, which contrasts sharply with the finding in the existing literature that financial structure generally does not matter.

The Lag in Effect of Inflation Targeting and Policy Evaluation

The lag in effect of monetary policy contains vital information for the policy evaluation. Allowing for a time-varying treatment effect, we show that Inflation Targeting (IT) effectively lowers inflation for both developed and developing countries. Developed countries reach their targets rapidly with a 2-year lag in effect. Developing countries, however, reduce inflation gradually towards their targets and do not reach their ultimate goal by the end year of 2007.

The Effect of ESCO s on Carbon Dioxide Emissions

Proponents of energy service companies (ESCOs) argue that these firms provide a crucial instrument for delivering improved energy efficiency in public and private sectors, thus contributing to carbon dioxide (CO2) emissions reduction around the world. Do ESCOs reduce CO2 emissions? To answer this question, we develop an estimating equation, which approximates the IPAT model, from a simple model of production. Based on the modified dynamic IPAT model, using the panel data of 129 countries over the period 1980 to 2007, we provide significant evidence to show that the ESCOs effectively reduce CO2 emissions and this effect increases over time. These findings also prove robust to the inclusion of a set of control variables, different dates of the first ESCO, and the Kyoto Protocol. Finally, we discuss energy policy implications.

Output Growth and Its Volatility: The Gold Standard through the Great Moderation

This study examines the relationship between U.S. output growth and its volatility over the period 1876:I to 2012:II. We adjust the data for outliers and structural breaks. We employ generalized autoregressive conditional heteroskedasticity (GARCH) and exponential GARCH (EGARCH) specifications. Normality and homoskedasticity appear only in the GARCH or EGARCH model that corrects for the outliers. When including the break in the mean equation, high volatility persistence remains. After also accommodating the breaks in the variance equation, the integrated GARCH effect proves spurious, either for the symmetric or the asymmetric model. Finally, our empirical results suggest that the finding of higher output growth volatility stimulating output growth and higher output growth reducing its volatility obtained from the symmetric GARCH-in-mean (GARCH-M) model also proves spurious as a result of the emergence of an asymmetric effect. Our more appropriately specified asymmetric EGARCH-M model suggests positive volatility-in-mean and level effects in the long-period real gross national product series.

Banking Market Structure, Liquidity Needs, and Industrial Growth Volatility

While the existing literature acknowledges the effect of banking structure on industrial growth as well as the effect of financial development on industrial growth and its volatility, we examine whether banking structure, given bank (financial) development, exerts any nontrivial effect on industrial growth volatility. We show that bank concentration magnifies industrial growth volatility, but reduces the volatility in sectors with higher external liquidity needs. The reduction in industrial growth volatility mostly reflects the smoothing in the variance of real value added per firm growth. Finally a variety of sensitivity checks show that our findings remain for different model specifications, banking market structure measures, liquidity needs indicators, and omitted variables.

Does a Threshold Inflation Rate Exist?: Quantile Inferences for Inflation and Its Variability

Using quantile regressions and cross-sectional data from 152 countries, we examine the relationship between inflation and its variability. We consider two measures of inflation – the mean and median – and three different measures of inflation variability – the standard deviation, relative variation, and median deviation. All results from the mean and standard deviation, the mean and relative variation, or the median and the median deviation support both the hypothesis that higher inflation creates more inflation variability and that inflation variability raises inflation across quantiles. Moreover, higher quantiles in both cases lead to larger marginal effects of inflation (inflation variability) on inflation variability (inflation). We particularly consider whether thresholds for inflation rate or inflation variability exist before finding such positive correlations. We find evidence of thresholds for the effect of inflation (inflation variability) on inflation variability (inflation). That is, for low inflation (inflation variability) countries, inflation (inflation variability) does not affect inflation variability (inflation). Finally, a series of robustness checks, including a set of additional explanatory variables as well as controlling for potential endogeneity with instrumental variables, leaves our findings generally unchanged.