Do real interest rates converge across East Asian countries based on China?

This study applies the sequential panel selection method (SPSM), proposed by Chortareas and Kapetanios (2009), to assess the non-stationary properties of the real interest rates relative to China for ten East Asian countries. SPSM can classify the whole panel into a group of stationary series and a group of non-stationary series. We clearly identify how many and which series in the panel are stationary processes and provide robust evidence to indicate that RIRP holds true for five countries. It implies that the choices and effectiveness of the monetary and fiscal policies in the East Asian economies will be highly influenced by external factors originating from China. Also, our findings point out that real interest rate convergence relative to China is mean reverting toward RIRP equilibrium values in a non-linear way.     

Estimating average economic growth in time series data with persistency

This paper studies estimation of average economic growth in time series models with persistency. In particular, a joint estimation of the trend coefficient and the autoregressive parameter is considered. An analysis on the proposed estimator is provided. Our analysis is also extended to the case with general disturbance distributions. A nonlinear M estimator and a class of partially adaptive M estimators which adapt themselves with respect to a measure of the tailthickness are considered. The joint estimator and its partially adapted version are compared with several conventional estimators. Monte Carlo experiments indicate that the proposed estimators have good finite sample performance. We use the proposed estimation procedure to estimate the growth rates for real GNP and consumer price index in 40 countries.     

Is per capita real GDP stationary in China? Sequential panel selection method

This paper investigates the time-series properties of per capita real GDP in China. The Sequential Panel Selection Method (SPSM) using the Panel KSS test with a Fourier function, a novel approach to panel unit testing, is applied to the data on 31 Chinese provinces over the period of 1979 to 2009. The SPSM classifies the whole panel into the group of stationary and non-stationary series, which identifies how many and which series are characterized by stationary processes. The results indicate that the per capita real GDP are non-stationary in all of these 31 regions in China, providing important policy implications.     

CO2 emissions converge in the 50 U.S. states — Sequential panel selection method

This study applies the sequential panel selection method (SPSM) procedure proposed by Chortareas and Kapetanios (2009) to investigate the time-series properties of CO₂ emissions for 50 U.S. states during the 1990 to 2010 period. SPSM classifies the whole panel into a group of stationary series and a group of non-stationary series. In doing so, we could clearly identify how many and which series in the panel are stationary processes. Empirical results from the SPSM using the panel KSS unit root test (Ucar and Omay, 2009) with a Fourier function, indicate that CO₂ emissions only converge in 12 out of the 50 U.S. states in our analysis.     

Do real interest rates converge across Latin american countries?

In this study, we apply the Sequential Panel Selection Method (SPSM), proposed by Chortareas and Kapetanios (Journal of Banking and Finance 33:390–404, 2009), to investigate and assess the non-stationary properties of the real interest rate parity (RIRP) for fourteen Latin American countries. Utilizing the SPSM, we can classify the entire panel into a group of stationary series and a group of non-stationary series. We clearly identify how many and which series in the panel are stationary processes and provide robust evidence that clearly indicate RIRP holds true for ten countries. Our findings note that these countries’ real interest rate convergence is a mean reversion toward RIRP equilibrium values in a non-linear way. Our results have important policy implications for these Latin American countries under study.     

Testing for Seasonal Stability in Unemployment Series: International Evidence

Recently, it has been shown that seasonal and business cycles are related and a similar economic mechanism is at work in producing both types of cycles (Miron 1996). Thus, an analysis of seasonal fluctuations sheds light on the nature of the business cycle. This paper uses the classical test developed by Hylleberg et al. and the LM-type tests proposed by Canova and Hansen (1995) to investigate seasonal behavior in the unemployment series of Australia, Canada, Japan, New Zealand, the US and a number of OECD countries. The main findings are that the Australian, Austrian and Canadian series are non-stationary at all seasonal frequencies, French, Japan, the NZ and the UK series are stationary at all seasonal frequencies and the USA series is stationary only at the annual frequency. The test results for other series are mixed, suggesting that further analysis is required to reach a definite conclusion. The series, except for France, Japan, New Zealand and the UK, appear to possess unstable seasonal patterns, indicating changing business cycle conditions.     

Sunspot cycles

Summary. This paper shows new properties about the equilibria of a stationary OG economy by establishing a connection between its stationary equilibria and those of a finite economy, with and without extrinsic uncertainty. Specifically, it shows the countability and local uniqueness with respect to the sup metric of the so-called sunspot cycles introduced here, that encompass both the deterministic cycles and the usual finite Markovian stationary sunspot equilibria. These sunspot cycles are, moreover, able to generate, at a lower cost in terms of assumptions than other sunspot equilibria, time series with the recurrent but irregular fluctuations typical of economic time series. Received: July 26, 2001; revised version: March 5, 2002 RID="*" ID="*" I want to thank an anonymous referee for comments that have helped greatly to improve this paper, as well as the comments about its contents received from several audiences in different seminars and conferences (the Economic Theory seminar of the University of Pennsylvania, the 2001 Meeting of the Econometric Society held at New Orleans, the 2000 Econometric Society World Congress, the 2000 Society for Economic Design Conference) and from comments to a previous paper, Dávila [10], specially from Jim Peck at the 1997 Workshop on General Equilibrium held at the University of Venice, that eventually lead to this one.     

Estimation of Censored Regression Model: A Simulation Study

We investigate the finite sample performance of several estimators proposed for the panel data Tobit regression model with individual effects, including Honoré estimator, Hansen’s best two-step GMM estimator, the continuously updating GMM estimator, and the empirical likelihood estimator (ELE). The latter three estimators are based on more conditional moment restrictions than the Honoré estimator, and consequently are more efficient in large samples. Although the latter three estimators are asymptotically equivalent, the last two have better finite sample performance. However, our simulation reveals that the continuously updating GMM estimator performs no better, and in most cases is worse than Honoré estimator in small samples. The reason for this finding is that the latter three estimators are based on more moment restrictions that require discarding observations. In our designs, about seventy percent of observations are discarded. The insufficiently few number of observations leads to an imprecise weighted matrix estimate, which in turn leads to unreliable estimates. This study calls for an alternative estimation method that does not rely on trimming for finite sample panel data censored regression model.     

Purchasing power parity in transition countries: Sequential panel selection method

This study applies the Sequential Panel Selection Method (SPSM), proposed by Chortareas and Kapetanios (2009) to test the validity of long-run purchasing power parity (PPP) for a sample of 14 transition countries, using real effective exchange rates, from 1994 to 2012 (for both monthly and quarterly data). SPSM classifies the whole panel into a group of stationary series and a group of non-stationary series. In doing so, we can clearly identify how many and which series in the panel are stationary processes. Empirical results from the SPSM using the Panel KSS unit root test (Ucar and Omay, 2009) with a Fourier function indicate that PPP holds true for most of these transition countries studied. Our results have important policy implications for these transition countries under study.     

Market Efficiency and Apparent Unit Roots: An Application to Exchange Rates

Prices in efficient markets are influenced by trading based on past patterns in the series. This induces parameter instability and near-random-walk behaviour in any time-series model of such data. Simulation results suggest that this parameter instability makes stationary series more likely to be erroneously classified as nonstationary, according to standard unit root or stationarity tests. It is shown that individual real exchange rate series appear individually non-stationary, especially for tests based on a null of stationarity, even though they appear stationary when treated as a panel.     

Rationality tests in the presence of instabilities in finite samples

The importance of expectations in modern macroeconomic models and in particular of policy makers expectations for forward looking policy rules has generated a lot of interest in time series of professional forecasts (including central bank staff forecasts). This has spawned a large literature on the evaluation of forecasts that are not model based or where the model is unknown. Although, the available time series of historical forecasts are typically short, this literature has so far mostly disregarded the small sample properties of the proposed tests and estimators. In this paper we fill this gap in the literature, focusing on a set of recently proposed rationality tests for unstable environments. Using a Monte Carlo study we demonstrate that the asymptotic tests are substantially oversized in finite samples including any sample size that is practically available. We provide finite sample adjusted critical values, that allow those tests to be properly applied to sample sizes of typically available forecasts such as the Survey of Professional Forecasters, the Federal Open Market Committee. The critical values we provide will help to avoid false rejections using those data.     

An investigation into a non-linear stochastic trend model

The paper explores the empirical properties of a non-linear stochastic trend model which can be viewed as an intermediate case between a linear and a log-linear trend model. I assess the small sample distribution of the ML estimator by Monte Carlo simulations and use it to model some typical macroeconomic time series. The non-linear trend model turns out to be an important tool which warrants further analysis. I also compute impulse response functions and compare them with those obtained from a conventional linear model. First version received: August 1997/final version received: June 1998     

A note on variance estimation for the Oaxaca estimator of average treatment effects

We derive the limiting distribution of the Oaxaca estimator of average treatment effects studied by Kline (2011). A consistent estimator of the asymptotic variance is proposed that makes use of standard regression routines. It is shown that ignoring uncertainty in group means will tend to lead to an overstatement of the asymptotic standard errors. Monte Carlo experiments examine the finite sample performance of competing approaches to inference.     

Stabilizing Taylor rules and determinacy under unit root supply shocks: A re-examination

I revisit the stabilizing and determinacy properties of Taylor-type policy rules in the canonical New Keynesian model when allowing for a unit root in the supply shock process. While able to offset inflationary pressure from non-stationary disturbances, interest-rate feedback rules that are unresponsive to fluctuations in the output gap necessarily produce unstable dynamics and explosive volatility for the latter. Specifically, rules fulfilling the Taylor principle are found to enforce the unique (non-stationary) equilibrium featuring well-anchored inflation expectations and immunity to sunspots; yet there exists no equilibrium predicting stationary behavior for both the inflation and output gap series, irrespective of whether the policy stance induces determinacy or indeterminacy. I show this property survives the adoption of forecast-based instrument rules, and also explore the relationship between Taylor-type rules and optimal discretionary policies in this particular New Keynesian environment.     

Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve

When a linear model suffers from endogeneity, a conventional solution is to use external instrumental variables. Sometimes, however, there are either no suitable external IVs or they are of poor quality. This paper constructs an internal instrumental variable from the time trend in the endogenous regressor without using any external IVs. We show that under some mild conditions this new trend IV estimator has desirable asymptotic properties, and also provide a robust Durbin-Wu-Hausman specification test to demonstrate the necessity of the IV method. Monte Carlo simulations show that the estimator and the test have good finite sample performance. In the end, we apply the trend IV estimator to the US New Keynesian Phillips Curve and find that it works as well as the usual external IVs in the literature.     

Enhancing the local power of IVX-based tests in predictive regressions

IVX estimation is used increasingly often in predictive regressions with regressors of unknown persistence. While not exhibiting the second-order bias the OLS estimator has in this setup, IVX estimators have reduced rates of convergence when the regressors are highly persistent. The reduced convergence rates may sometimes lead to power losses in finite samples when testing for no predictability, for instance. The note discusses a simple way of improving the local power of IVX-based tests, consisting of augmenting the predictive regression with the lagged dependent variable. This implies a feed-back loop which strengthens the signal of the IVX instrument without changing its dynamic properties. The proposed augmentation works best when the power loss of IVX would have been maximal compared to the infeasible OLS-based test.     

Wage Setting, Wage Curve and Phillips Curve: The Italian evidence

The purpose of this paper is to investigate some issues of wage setting in order to assess if nominal inertia and wage flexibility characterise the Italian supply side, using multivariate cointegration models. Our estimates indicate that an explicit distinction between stationary and non-stationary variables and a joint analysis of long-run and short-run structure is crucial for achieving clearer results. To this end, we use quarterly time series data for industry sector 1976:1–1993:4. Interesting results have been found concerning the empirical evidence of a long-run wage curve and the existence of a Phillips curve, through adopting alternative order reduction of the I(2) wage and price variables. Moreover, some insights on regional (North-South) unemployment effects are pointed out and discussed.     

Accounting for missing data in M-estimation: a general matching approach

This paper addresses M-estimation of conditional mean functions when observations are missing at random. The usual approach of correcting for missing data, when the missing data mechanism is ignorable, is inverse probability weighting (IPW). An alternative semiparametric M-estimator which involves local polynomial matching techniques is proposed and its asymptotic distribution is derived. Like IPW, the proposed estimation approach has a double robustness property for the estimation of unconditional means. Monte Carlo evidence suggests slightly better finite sample properties of the semiparametric M-estimator relatively to IPW. A version of the proposed estimator is applied to estimate the impact of noncognitive skills on wages in Germany for two different educational treatment regimes.     

Stationary and Non-stationary Simultaneous Switching Autoregressive Models with an Application to Financial Time Series

A common observation among economists on many economic time-series, including major financial time-series, is the asymmetrical movement between the downward phase and the upward phase of their sample paths. Since this feature of time irreversibility cannot be described by the Gaussian ARMA, ARIMA or ARCH time-series models, we propose stationary and non-stationary simultaneous switching autoregressive (SSAR) models, which are nonlinear switching time-series models. We discuss some properties of these time-series models and the estimation method for their unknown parameters. The asymmetrical conditional heteroscedasticity can be easily incorporated into the SSAR models. We also report a simple empirical result on Nikkei 225 Spot and Futures indices by using a non-stationary SSAR model.
JEL Classification Numbers: C22, C32.     

An analysis of extreme movements of exchange rates of the main currencies traded in the Foreign Exchange market

This article analyses the extreme movements of exchange rates of the seven main currencies traded in the Foreign Exchange market against the US dollar: Euro, British pound, Canadian dollar, Japanese Yen, Swiss franc, Australian dollar and New Zealand dollar by using tail index indicators. Payaslio?lu (2009) considers the case of the Turkish exchange rate using the traditional Hill (1975) estimator as a tool. In this article, we employ also an alternative estimator proposed in Iglesias and Linton (2009) that is shown to have, in some cases, improved finite sample properties and it provides substantially different results versus the Hill estimator. We find that for the Euro, Japanese Yen, Swiss franc, Canadian, Australian and New Zealand dollars, the Hill estimator provides a better measure to analyse the extreme behaviour; while for the British pound, the Iglesias and Linton alternative estimator is superior by using Hausman-type tests of misspecification. Measures of value at risk are also provided for the seven markets. We also find that the largest estimated value at risk by far is for the Japanese Yen, followed by the Swiss franc, the Canadian dollar, the Euro, the New Zealand dollar and the Australian dollar. The UK pound has the smallest value at risk when extreme movements occur.