Sector-Level Disaggregate Stochastic Trends in Mexico’s Real Output

Our aim is to examine whether sectorial production shocks have predominated in Mexico’s long annual real output, and whether shocks from different sectors are correlated. We study the long-run movement and comovements of 6 production sectors, using long, low frequency data for the Mexican economy from 1921 to 1993 and Johansen’s (1991, 1995) method to test for cointegration, that is, the possibility of common stochastic shocks driving growth among sectors. Under cointegration, the idiosyncratic sectorial shocks cancel out and vanish, giving rise to a (possibly multiple) stochastic growth component common to all (some) sectors. We show that the sources of permanent innovations in Mexico’s real output are more likely to come from sector-group-specific sources rather than from either independent sector-specific technological shocks, or common aggregate permanent innovations.Sectorial Production, Sequential Unit Root Testing, Cointegration, Common Trends

Quasi purchasing power parity: Structural change in the Mexican peso/us dollar real exchange rate

This paper analyzes whether the real exchange-rate of the Mexican peso/US dollar revert to a long-run equilibrium value, and whether this value is unique. We use a method for testing stationarity, that allows for an unknown number of structural breaks in the level of the series. Using a long span of annual data covering the period 1925-1994, our results provide evidence favouring long-run Quasi-Purchasing Power Parity. In particular, we find that the real peso/dollar exchange rate has fluctuated stationarily around a 70 year long-run level, perturbed by a series of events, both domestic and external, in or around 1981.

Unit roots and multiple structural breaks in real output

Utilizing re-sampling. Methods, we present evidence on the rejection probabilities for difference-stationary and trend-stationary models for Mexico’s real and real per-capita annual gross domestic product. The trend stationary alternative allows for stationary fluctuations around a long-run trend function with endogenously determined multiple structural breaks, via global and sequential search methods. The number of breaks is determined using a unit-root rejection stopping rule and a parameter-constancy stopping rule.

Spurious Regression and Econometric Trends

This paper analyses the asymptotic and finite sample implications of different types of nonstationary behavior among the dependent and explanatory variables in a linear spurious regression model. We study cases when the nonstationarity in the dependent and explanatory variables is deterministic as well as stochastic. In particular, we derive the order in probability of the t-statistic in a linear regression equation under a variety of empirically relevant data generation processes, and show that the spurious regression phenomenon is present in all cases considered, when at least one of the variables behaves in a nonstationary way. Simulation experiments confirm our asymptotic results.Spurious regression, trends, unit roots, trend stationarity, structural breaks

A Note on the Dynamics of Persistence in US Inflation

Empirical research on the degree and stability of inflation persistence in the US has produced mixed results: some suggest high and unchanged persistence during the last few decades, while others argue in favor of a decline in persistence since the early 1980s. We show that post-WWII US inflation (monthly and quarterly) became highly persistent during the´Great Inflation´ period, and then switched back to a low persistence process during 1984, and has remained stationary until the present day.Inflation, Multiple change in persistence, Stationarity, Great inflation.

Spurious regression under broken trend stationarity

We study the phenomenon of spurious regression between two random variables when the generating mechanism for individual series follows a stationary process around a trend with (possibly) multiple breaks in its level and slope. We develop relevant asymptotic theory and show that spurious regression occurs independently of the structure assumed for the errors. In contrast to previous findings, the spurious relationship is less severe when breaks are present, whether or not the regression model includes a linear trend. Simulations confirm our asymptotic results and reveal that, in finite samples, the spurious regression is sensitive to the presence of a linear trend and to the relative locations of the breaks within the sampleSpurious regression, Structural breaks, Stationarity

Spurious regression under deterministic and stochastic trends

This paper analyses the asymptotic and finite sample implications of a mixed nonstationary behavior among the dependent and explanatory variables in a linear spurious regression model. We study the cases when the nonstationarity in the dependent variable is deterministic (stochastic), while the nonstationarity in the explanatory variable is stochastic (deterministic). In particular, we derive the asymptotic distribution of statistics in a spurious regression equation when one variable follows a difference stationary process (a random walk with and without drift), while the other is characterized by deterministic nonstationarity (a linear trend model with and without structural breaks in the trend function). We find that the divergence rate is sensitive to the assumed mixture of nonstationarity in the data generating process, and the phenomenon of spurious regression itself, contrary to previous findings, depends on the presence of a linear trend in the regression equation. Simulation experiments and real data confirm our asymptotic results.Unit roots, Trend stationarity, Structural breaks, Spurious regression

On the dynamics of inflation persistence around the world

We study the dynamics of inflation persistence in 45 countries for the period 1960-2008. We use a nonparametric unit root test robust to nonlinearities, error distributions, structural breaks and outliers, many of them typical features of inflation data, and a test for multiple changes in persistence, which decomposes the sample information between adjacent I(0) and I(1) periods. We find that (1) With very few exceptions, inflation around the world rejects a unit root, (2) for several countries there is evidence of significant changes in persistence, (3) bursts and drops in the level of inflation and in inflation persistence tend to coincide, (4) these drops occurred during “the Great Moderation” and during the adoption of inflation targeting. We conclude that inflation is characterized by either a stationary behaviour throughout the sample, or by switches of the type I(0)-I(1)-I(0). For all countries in our sample, any indication of nonstationarity seems to be temporary.Inflation, Multiple persistence change, Stationarity, Unit root tests, Unknown direction of change, Monetary policy

Spurious Regression and Trending Variables

This paper analyses the asymptotic and finite sample implications of different types of nonstationary behavior among the dependent and explanatory variables in a linear spurious regression model. We study cases when the nonstationarity in the dependent and explanatory variables is deterministic as well as stochastic. In particular, we derive the order in probability of the t-statistic in a linear regression equation under a variety of empirically relevant data generation processes, and show that he spurious regression phenomenon is present in all cases considered, when at least one of the variables behaves in a nonstationary way. Simulation experiments confirm our asymptotic results.Trend Stationarity, Structural Breaks, Spurious Regression, Unit Roots, Trends