Chih-Chuan Yeh

Okun's law in panels of countries and states

This article contributes to the empirical literature of Okuns law in three respects. First, in contrast to the limited data used in the existing studies, we employ two extensive (across countries and across states, i.e. within a country) panel data sets to investigate the validity of Okuns law. Second, the use of the Pooled Mean Group (PMG) estimator permits us not to pre-filter the data as often done in the current literature, and can take into account the possibility of cointegration between unemployment and output. Third, in addition to the short-run relationship or cyclical components between unemployment and output, we also estimate the long-run linkage between these two important variables. Empirical results show that unemployment and output are long-run cointegrated, irrespective of using country- or state-level data. Moreover, the unemployment-output linkages are found to be negative and highly significant both in the short- and long-run. Our results not only confirm the validity of Okuns law (in the short-run) but also point out that a similar tradeoff exists in the long run.

An appropriate test of the Kuznets hypothesis

The Kuznets hypothesis, that is, inequality first rises and then falls as the economy advances, is often tested by regressing inequality on income and its squared term (along with other determinants). Findings of a significantly negative coefficient on income and a significantly positive estimate on the quadratic term are commonly taken as evidence supporting the inverted-U Kuznets curve. Although intuitive, Lind and Mehlum (2010) argued that the conventional approach is flawed and proposed an appropriate test for a U-shaped association. We revisit the validity of the Kuznets hypothesis by applying the novel testing strategy of Lind and Mehlum (2010) to annual US data over the period 1917 to 2007. Inconsistent with the Kuznets hypothesis, the test results overwhelmingly reject the combined null hypothesis of an inverted-U or monotone relationship in favour of a U-shaped linkage between income inequality and economic development. Moreover, the results are robust to changes in inequality measures and functional specifications.

Inflation targeting on unemployment rates: a quantile treatment effect approach

This article explores the treatment effects of inflation targeting (IT) on unemployment rates across a large panel of 74 countries over the 1980–2010 period. By addressing the ‘self-selection’ problem of policy adoption via a variety of propensity score matching algorithms, we first find that, on average, IT exerts no discernible effect on unemployment rates in the full sample. However, when the full sample is split into subgroups, the results strongly indicate that the adoption of IT is associated with higher (lower) unemployment rate in the industrial (developing) countries. Further outcome from a novel quantile treatment effects approach points out that the higher the unemployment rate is in the first place, the more harmful (beneficial) the implementation of IT becomes in the industrial (developing) subsample.

Price level convergence across cities? Evidence from panel unit root tests

This article empirically tests for convergence in Consumer Price Indices (CPIs) across 17 major cities in the United States over the period 1918 to 2008. Although the conventional panel unit root tests generally fail to reject the null hypothesis of nonstationarity, the panel LM tests of Im et al. (2005), by taking the presence of structural breaks into account, find overwhelming evidence in support of the hypothesis of price convergence The main finding is confirmed even when we consider both the structural changes and the cross-sectional dependence by using the recent advanced panel unit root approach of Bai and Carrion-i-Silvestre (2009).

The effects of inflation targeting on Okun’s law

ABSTRACT This article provides the first empirical evidence that the adoption of inflation targeting (IT) matters for the extent of tradeoff between unemployment and output, that is Okun’s law. Our full sample results indicate that IT leads to a more negative Okun’s coefficient, suggesting that, for a given reduction of output, the introduction of IT is associated with a higher unemployment rate. Subsample analyses reveal that the whole sample results are mainly driven by the industrial subsample outcomes, not the developing counterparts. Our findings point out that IT not only influences macroeconomic variables per se but also affects the relationship between/among macroeconomic variables.

A quantile framework for analysing the links between inflation uncertainty and inflation dynamics across countries

In contrast to the conventional conditional mean approaches, this study uses quantile regression techniques to present some new statistical evidence on the links between inflation uncertainty and the level of inflation with cross-sectional data from 90 countries during the period 1961 to 2006. The results suggest that positive inflation shocks have stronger impact on inflation uncertainty which varies across the quantiles. Furthermore, popular time-series models are evaluated for their ability to reproduce measures of uncertainty and indicate similar results regarding the relationships between inflation and inflation uncertainty.

Inequality-growth nexus along the development process

Abstract The paper examines whether the effect of inequality on growth varies with the level of economic development. Using a comprehensive panel of annual data for the 48 contiguous US states over the period 1945–2004, we find overwhelming evidence in support of threshold effects in the relationship between inequality and growth. Our analysis shows that while the effect of inequality on growth is significantly negative at lower levels of development, this effect diminishes along the growth process and then turns significantly positive at higher levels of development. Quantitatively, the coefficient estimates imply that when real income per capita is below the threshold of

A reassessment of inequality and growth in the United States

12,140 (2004 US dollar), a one standard deviation increase in the share of income held by the top 1% of the population reduces the growth rate of real per capita income by 0.6479 percentage points. In contrast, when income per capita is above the threshold of

Joint determinations of inequality and growth

21,065 (2004 US dollar), a one standard deviation increase in the top percentile income share raises the rate of growth of real per capita income by 0.2561 percentage points.

A quantile inference of the Kuznets hypothesis

In a recent interesting paper, Frank (2009) investigated the long-run inequality–growth nexus with a large panel of annual data for the 48 states in the United States over the 1945 to 2004 post-war period. By implementing the Pooled Mean Group (PMG) estimators, Frank (2009) concluded that there is a significant and positive relationship between inequality and growth. However, we find that Frank (2009) was actually measuring the effect of inequality on economic development (proxied by the logarithm of the real state income per capita) rather than on economic growth (defined by the first difference of the logarithm of the real state income per capita). To this purpose, we suggest a more adequate specification to reassess the relationship using the same data set and estimation technique. The fresh empirical results indicate that the inequality–growth connection continues to hold in a positive and significant manner, and the findings are robust to alternative lag order structures and income inequality measures.