Chi Young Choi

How Useful are Tests for Unit-Root in Distinguishing Unit-Root Processes from Stationary but Non-Linear Processes?

Standard unit-root tests are known to be biased towards the non-rejection of a unit-root when they are applied to time series with non-linear dynamics. Unfortunately, not much is known about the source of the power loss mainly because the analysis on nonstationarity and nonlinearity to this date has been fragmentary. By means of a Monte Carlo study, the current paper investigates the finite sample performance of five popular unit-root tests against a wide class of non-linear dynamic models. In contrast to the common perception, our simulation results suggest that what determines the power of unit-root tests is not the specific type of nonlinearity in the alternative model, but how far the alternative model is away from the unit-root process. The presence of nonlinearity seems immaterial to the performance of unit-root tests if the non-linear process is far away from the unit-root process, which is in line with the fact established in linear framework. Among the five tests under study, the ADF test outperforms when the sample size is relatively small while the inf-t due to Park and Shintani (2005) is more powerful for relatively large sample size regardless of the form of true models. We then illustrate the empirical relevance of our analysis by reexamining the issue of mean reversion in real interest rates, often referred to the Fisher hypothesis. Copyright Royal Economic Society 2007

Bias Reduction in Dynamic Panel Data Models by Common Recursive Mean Adjustment

The within-group estimator (same as the least squares dummy variable estimator) of the dominant root in dynamic panel regression is known to be biased downwards. This article studies recursive mean adjustment (RMA) as a strategy to reduce this bias for AR(p) processes that may exhibit cross-sectional dependence. Asymptotic properties for N,T→∞ jointly are developed. When ( log 2T)(N/T)→ζ, where ζ is a non-zero constant, the estimator exhibits nearly negligible inconsistency. Simulation experiments demonstrate that the RMA estimator performs well in terms of reducing bias, variance and mean square error both when error terms are cross-sectionally independent and when they are not. RMA dominates comparable estimators when T is small and/or when the underlying process is persistent.

Inflation Targeting and Relative Price Variability: What Difference Does Inflation Targeting Make?

This article studies the effects of inflation targeting (IT) on relative price variability (RPV) using a data set of twenty countries comprising both targeters and nontargeters. We find that a decline in mean inflation after IT adoption is not necessarily associated with a similar fall in RPV and that what matters most for the structural changes in RPV is the initial inflation regime prior to the adoption of IT rather than IT adoption itself. IT adoption impacts the shape of the underlying relationship between inflation and RPV in countries with initially high inflation rates, moving it from monotonic to the U-shaped profile observed consistently for countries with low-inflation regimes. The minimum point of this U-shaped curve is indicative of the publics expectations of inflation and is very close to the announced target for inflation in most of the countries we study.

On the performance of popular unit-root tests against various nonlinear dynamic models : A simulation study

ABSTRACT There is a widespread perception that standard unit-root tests have poor discriminatory power when they are applied to time series with nonlinear dynamics. Via Monte Carlo simulations this study re-examines the finite sample properties of selected univariate tests for unit-root and stationarity under a broad class of nonlinear dynamic models. Our simulation experiments produce a couple of interesting findings. First, performance of tests is driven by the degree of underlying persistence rather than the nonlinear dynamics per se. Tests under study exhibit reasonable performance for nonlinear models with mild persistence, while the accuracy of inference deteriorates substantially when the models are highly persistent regardless of the linearity. Second, when it comes to deciding which one to identify first between linearity and stationarity, our results suggest to conduct linearity test first to enhance the reliability of test inference.

Monetary policy regime change and regional inflation dynamics: looking through the lens of sector-level data for Korea: Monetary policy regime change and regional inflation dynamics

This paper explores the impact of the adoption of inflation targeting (IT) on the dynamics of city-level inflation in Korea using both aggregate and sector-level data. When looking at aggregate regional inflation, we find that the mean, volatility and persistence fell in all cities in the wake of the monetary policy regime change, consistent with other evidence in the literature. We also note a narrowing of the dispersion of regional inflation across cities and a greater degree of regional co-movement. Delving more deeply into the disaggregate data reveals additional insights however. For most of the changes we observe in the dynamics of regional inflation, we find that the aggregate effects are being driven primarily by sectors that fall into the ‘Services’ category. We posit that the impact of better anchored inflationary expectations is primarily on the less-traded services sectors of the economy, where the domestic monetary policy framework has a relatively larger influence compared with globally-traded commodities. When it comes to the increased co-movement observed across regions under IT regime, however, it is the ‘Commodities’ sectors rather than ‘Services’ that are responsible, probably because services inflation becomes relatively more influenced by local factors once it has stabilized within the target range. We show that this sectoral heterogeneity can be explained by the difference in price stickiness such that sectors in which prices are adjusted less frequently tend to have a larger response under the new monetary policy regime.

Geographic Inequality of Economic Well-being among U.S. Cities: Evidence from Micro Panel Data

We analyze the geographic inequality of economic well-being among U.S. cities by utilizing a novel measure of quantity based product-level economic well-being, i.e., the number of goods and services that can be purchased by consumers with an average city wage. We find a considerable cross-city dispersion in the economic well-being and the geographic dispersion has been on the steady rise since the mid-1990s for most goods and services under study. Strong geographic correlations exist in the local economic well-being and our empirical analysis based on a Global VAR (GVAR) model suggests that national shocks are an important source behind it. On average, about 30-35% of the variance of local well-being is explained by common national shocks, but the impact of common national shocks varies considerably across products, albeit to a lesser extent across cities. Nationwide unemployment shock, for example, has a stronger effect in the products whose prices are adjusted more frequently and in the cities that have a larger fraction of high-skill workers. Taken together, our results indicate that the geographic inequality of economic well-being observed in the U.S. has proceeded over time mainly through the products with more flexible price adjustments and in the cities with higher concentration of skilled workers.

Monetary Policy Regime Change and Regional Inflation Dynamics: Looking Through the Lens of Sector-Level Data for Korea

This paper explores the impact of the adoption of inflation targeting (IT) on the dynamics of city-level inflation in Korea using both aggregate and sector-level data. When looking at aggregate regional inflation, we find that the mean, volatility and persistence fell in all cities in the wake of the monetary policy regime change, consistent with other evidence in the literature. We also note a narrowing of the dispersion of regional inflation across cities and a greater degree of regional co-movement. Delving more deeply into the disaggregate data reveals additional insights however. For most of the changes we observe in the dynamics of regional inflation, we find that the aggregate effects are being driven primarily by sectors that fall into the ‘Services’ category. We posit that the impact of better anchored inflationary expectations is primarily on the less-traded services sectors of the economy, where the domestic monetary policy framework has a relatively larger influence compared with globally-traded commodities. When it comes to the increased co-movement observed across regions under IT regime, however, it is the ‘Commodities’ sectors rather than ‘Services’ that are responsible, probably because services inflation becomes relatively more influenced by local factors once it has stabilized within the target range. We show that this sectoral heterogeneity can be explained by the difference in price stickiness such that sectors in which prices are adjusted less frequently tend to have a larger response under the new monetary policy regime.

Heterogeneous Response of Disaggregate Inflation to Monetary Policy Regime Change: What Can Be Learned from Canada’s Adoption of Inflation Targeting?

This paper explores the impact of monetary policy regime change on sectoral and regional inflation by analyzing the case of Canada and its adoption of inflation targeting (IT). Using disaggregated CPI data for Canada from 1978, we find that responses to the change in the monetary policy framework are quite heterogeneous, particularly across sectors. While inflation series in the traditionally volatile commodity sectors exhibit weak responses to the regime change, those in the so-called core sectors are highly responsive. This pattern is evident in both national and provincial level data, indicating that it is the core sectors that are crucial for the transmission of a monetary policy regime change. Further analysis based on a common factor model reveals that common shocks, such as those associated with the monetary policy framework, account for only a small portion of the variation in sectoral inflation, and that their relative importance has decreased after IT adoption in many core sectors. Interestingly, considerable variation exists even across the core sectors in the strength of the regime change effect. We document that this heterogeneity is meaningfully correlated with some measurable sector-specific characteristics; sectors with a lower degree of prices stickiness and a lower degree of tradability appear more sensitive to the change in monetary policy regime.