Heejoon Kang

SPURIOUS PERIODICITY IN INAPPROPRIATELY DETRENDED TIME SERIES

Econometric analysis of time series data is frequently preceded by regression on time to remove a trent component in the date. The resulting residuals are then treated as a stationary series to which procedures requiring stationarity, such as spectral analysis, can be applied. The objective is often to investigate the dynamics of transitory movements in the systems, for example, in econometric models of the business cycle. When the data does consist of a deterministic function of time plus a stationary error then regression residuals will clearly be unbiased estimates of the stationary component. However, if the data is generated by (possibly repeated) summation of a satisfactory and inevitable process then the series cannot be expressed as a deterministic function of time plus a stationary deviation, even though a least squares trend line and the associated residuals can always be calculated for any given finite sample. In a recent paper, Chan, Hayya, and Ord (1977) hereafter CHO) were able to show that a residuals from linear regression of a realization of a random walk (the summation of a purely random series) on time have autocovariances which for given lag are a function of time and thereafter that the residuals are not stationary. Further, CHO established that the expected sample autocovariance function (the expected autocovariances for given lag averaged over the time interval of the sample) is a function of sample size as well as lag and therefore an artifact of the detrending procedure. This function is characterized by CHO in their figure 1 as being effectively linear in lag (although the exact function is a fifth degree polynomial) with the rate of decay from unity at the origin depending inversely on sample size.

Bilateral Trade and Political Conflict/Cooperation: Do Goods Matter?

This article investigates Granger causality between political conflict/cooperation and bilateral trade. The measures of conflict/cooperation are constructed by accumulating daily events and splicing the two datasets of the Conflict and Peace Data Bank and the World Events Interaction Survey. Trade data from the United Nations include ten commodity groups as well as total trade. Quarterly data are analyzed from the very early 1970s to the early 1990s for four dyads of USA-USSR, USA-China, Turkey-Greece, and Egypt-Israel. Yearly data are investigated from the early 1960s to the early 1990s for 16 dyads. Granger causality between bilateral trade and conflict/cooperation is generally reciprocal in most goods and dyad dependent, but independent of whether or not two countries are political rivals. For USA-USSR and USA-China, however, there is a tendency for bilateral trade to increase in some goods when political relations improve. For USA-USSR, in particular, causality from conflict to trade is pronounced in more goods than causality from trade to conflict. While the effect of cooperation in these dyads is mostly positive, the effect of an increase of trade on conflict is generally ambiguous. For 20 dyads collectively, conflict/cooperation tends to Granger-cause bilateral trade in minerals, iron and steel, fuels, basic manufactures and control and scientific equipment; whereas bilateral trade somewhat more frequently Granger-causes conflict/cooperation in food and live animals, beverages and tobacco, and machines and transport equipment. The concept of strategic goods, much debated in the literature, is further discussed in light of these results. The general result of reciprocal Granger causality calls for a model in which both bilateral trade and conflict/cooperation are simultaneously determined. Such a simultaneous equations model is briefly sketched.

The Effects of Detrending in Granger Causality Tests

Nonstationary time series are frequently detrended in empirical investigations by regressing the series on time or a function of time. The effects of the detrending on the tests for causal relationships in the sense of Granger are investigated using quarterly U.S. data. The causal relationships between nominal or real GNP and M1, inferred from the Granger–Sims tests, are shown to depend very much on, among other factors, whether or not series are detrended. Detrending tends to remove or weaken causal relationships, and conversely, failure to detrend tends to introduce or enhance causal relationships. The study suggests that we need a more robust test or a better definition of causality.

International Conflict and Cooperation: Splicing COPDAB and WEIS Series

Events data sets are used extensively in the study of international relations. The Conflict and Peace Data Bank (COPDAB) data from 1948 to 1978 and the World Events Interaction Survey (WEIS) data since 1966 are the two events data sets that are most widely used. In this article a simple method is proposed to combine (or splice) COPDAB and WEIS events time series in order to create a single spliced time series from 1948 to 1993. Past research on the compatibility of COPDAB and WEIS is inconclusive: some authors claim that COPDAB and WEIS are compatible, while others claim they are not. We here investigate six dyads and show that the compatibility of WEIS and COPDAB depends on the particular dyad in question, but the two series are generally compatible so that COPDAB and WEIS can be spliced into one time series in five out of six dyads. (One dyad contains too many periods of missing reports in the data.) The article is organized in the following sections: The COPDAB and WEIS data sets are described in the first section. The second section reviews the literature about the COPDAB and WEIS compatibility. The third section outlines our approach to the question of compatibility. Statistical tests for compatibility and the method for splicing the two data sets are provided in the fourth section. A summary of our findings is provided in the last section.

The optimal lag selection and transfer function analysis in Granger causality tests

Abstract The conventional selection of lag lengths through the final prediction error criterion is shown to be inadequate in the test of Granger causality. In this paper, lag terms are selected optimally in the most efficient forecast equations that are obtained from univariate and transfer function analyses. The reduction in the forecasting error variances from the two analyses is used to test Granger causality. The new procedure is applied to test for the causality between the industrial production and the leading indicator and that between the consumer price index and the producer price index in the United States.

A Simultaneous-Equations Model of Trade, Conflict, and Cooperation

A simultaneous-equations model is developed for the reciprocal relationship among bilateral trade value, conflict, and cooperation by modeling the actions of exporters, importers, and governments. The model is estimated separately for each of the dyads among the US, the USSR, China, Japan, and (West) Germany for the yearly data from 1948 to 1992. The direction of the effects of conflict or cooperation on trade and that of trade on conflict or cooperation are generally mixed, as expected. Certain reciprocal relationship patterns emerge depending on whether countries belong to the East or West block.

International Trade Efficiency, the Gravity Equation, and the Stochastic Frontier

In the gravity equation of international trade, bilateral trade flows are regressed on trading partners’ income and the distance that separates them along with other variables. This widely used equation is traditionally estimated by the ordinary least squares method. We employ an alternative technique of stochastic frontier estimation to assess the potential bilateral trade flows from the same gravity equation. Countries are shown to have low efficiencies in their international trade as the predicted trade from frontier estimation is generally far greater than actual trade. Trade efficiencies are computed and ranked for individual countries, ten geographical regions, and eleven regional trade agreements.

Random walk and monetary causality in five exchange markets

Abstract Time series behavior of monthly spot exchange rates for the French franc, the Deutsche mark, the Italian lira, the Japanese yen, and the UK pound, all priced in relation to the US dollar, shows the robustness of the random walk hypothesis. Incremental efficiency is investigated by a new test procedure, based on the reduction of the forecast error variance, which is a direct implementation of the definition of Granger causality. Exchange markets are found to be not only money efficient, but also monetary efficient in that they are efficient with respect to real income and market interest rates in addition to money stock.

Univariate ARIMA Forecasts of Defined Variables

Many important variables in business and economics are neither measured nor measurable but are simply defined in terms of other measured variables. For instance, the real interest rate is defined as the difference between the nominal interest rate and the inflation rate. There are two ways to forecast a defined variable: one can directly forecast the variable itself, or one can derive the forecast of the defined variable indirectly from the forecasts of the constituent variables. Using Box-Jenkins univariate time series analysis for four defined variables—real interest rate, money multiplier, real GNP, and money velocity—the forecasting accuracy of the two methods is compared. The results show that indirect forecasts tend to outperform direct methods for these defined variables.

Exploring multi-country dynamic relations between trade and conflict

Most previous studies use a dyad as the unit of analysis and ignore the simultaneity of trade and conflict. The goal of this paper is to find out whether multi‐country trade and conflict relations are statistically significant and the nature of those relations. We employ a multi‐country, simultaneous framework, using the United States‐Soviet Union‐(West) Germany triangle as an example. The empirical analysis, from the first quarter of 1963 to the last quarter of 1991, demonstrates that trade and conflict are significantly interrelated, with positive reciprocity and inertia. Moreover, we find that dyadic flows strongly affect other dyads. The nature of these inter‐dyadic effects depends on particular dyads, but both inter‐ and intra‐dyad effects are statistically significant.