This paper develops a regression limit theory for nonstationary panel data with large numbers of cross section Ž n. and time series Ž T. observations. The limit theory allows for both sequential limits, wherein T� � followed by n��, and joint limits where T, n�� simultaneously; and the relationship between these multidimensional limits is explored. The panel structures considered allow for no time series cointegration, heterogeneous cointegration, homogeneous cointegration, and near-homogeneous cointegration. The paper explores the existence of long-run average relations between integrated panel vectors when there is no individual time series cointegration and when there is heterogeneous cointegration. These relations are parameterized in terms of the matrix regression coefficient of the long-run average covariance matrix. In the case of homogeneous and near homogeneous cointegrating panels, a panel fully modified regression estimator is developed and studied. The limit theory enables us to test hypotheses about the long run average parameters both within and between subgroups of the full population.

An asymptotic theory is developed for nonlinear regression with integrated processes. The models allow for nonlinear effects from unit root time series and therefore deal with the case of parametric nonlinear cointegration. The theory covers integrable and asymptotically homogeneous functions. Sufficient conditions for weak consistency are given and a limit distribution theory is provided. The rates of convergence depend on the properties of the nonlinear regression function, and are shown to be as slow as n1�4 for integrable functions, and to be generally polynomial in n1�2 for homogeneous functions. For regressions with integrable functions, the limiting distribution theory is mixed normal with mixing variates that depend on the sojourn time of the limiting Brownian motion of the integrated process.

To investigate how a fixed exchange rate affects monetary policy, this paper classifies countries as pegged or nonpegged and examines whether a pegged country must follow the interest rate changes in the base country. Despite recent research which hints that all countries, not just pegged countries, lack monetary freedom, the evidence shows that pegs follow base country interest rates more than nonpegs. This study uses actual behavior, not declared status, for regime classification; expands the sample including base currencies other than the dollar; examines the impact of capital controls, as well as other control variables; considers the time series properties of the data carefully; and uses cointegration and other levels-relationship analysis to provide additional insights.

We propose and test a novel economic mechanism that generates stock return predictability on both the time series and the cross section. In our model, investors’ income has two sources, wages and dividends, that grow stochastically over time. As a consequence, the fraction of total income produced by wages changes over time depending on economic conditions. We show that as this fraction fluctuates, the risk premium that investors require to hold stocks varies as well. We test the main implications of the model and find substantial support for it. A regression of stock returns on lagged values of the labor income to consumption ratio produces statistically significant coefficients and adjusted R 2 ’s that are larger than those generated when using the dividend price ratio. Tests of the cross sectional implication find considerable improvements on the performance of both the conditional CAPM and CCAPM when compared to their unconditional counterparts.

Several authors have recently investigated the predictability of exchange rates by fitting a sequence of long-horizon error-correction/regressions.//We/show/that/in/small/to medium/samples/such/a/procedure/gives/rise/to/spurious/evidence/of/predictive/power./A simulation/study/demonstrates/that/even/when/using/this/technique/on/two/independent/series, estimates/and/diagnostic/statistics/suggest/a/high/degree/of/predictability/of/the/dependent variable./We/apply/a/simple/modification/of/the/long-horizon/regression/due/to/Jegadeesh (1991),/which/may/provide/more/accurate/inference/for/researchers/interested/in/comparing short/and/long-run/predictability of U.S. dollar exchange rates.

The authors are especially grateful to Michele Bullock for motivating the research. The paper has also benefited from many helpful comments by Adrian Blundell-Wignall, Philip Lowe and Tim Marney. Any errors are ours alone. The views expressed herein are those of the authors and do not necessarily reflect the views of This paper examines exchange rate pass-through for the prices of both imports and manufactured exports. It is found that, in the long run, exchange rate pass-through over the docks is complete for both classes of good. However, in the short run, responses to currency movements differ significantly. Differences occur with respect to the speed of pass-through and its pattern over time. Pass-through to import prices is found to be more rapid than that to manufactured export prices. However, evidence is presented of a recent and substantial increase in pass-through to manufactured export prices, in keeping with increased international integration. Conversely, existing patterns of exchange rate pass-through to import prices are found to accord with historical experience. The implications of this are discussed with respect to the

Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of Yule (1926) and Granger and Newbold (1974). Data mining for predictor variables interacts with spurious regression bias. The two effects reinforce each other, because more highly persistent series are more likely to be found significant in the search for predictor variables. Our simulations suggest that many of the regressions in the literature, based on individual predictor variables, may be spurious.

The opinions expressed here are the authors ’ and do not necessarily reflect those of the Bank of Canada. An earlier draft of this paper was presented under the title “The Determinant(s) of the U.S. Real Exchange Rate ” at the June 1993 Canadian Economic Association Meetings, Ottawa, Ontario, Canada. We are grateful to Alain DeSerres for his work on the earlier draft and to John Murray for his comments and suggestions. We acknowledge the use of the Bank of Canada’s RATS test procedures. The responsibility for errors is ours. ISSN 1192-5434

In the vehicle routing problem with time windows a number of identical vehicles must be routed to and from a depot to cover a given set of customers, each of whom has a specified time interval indicating when they are available for service. Each customer also has a known demand, and a vehicle may only serve the customers on a route if the total demand does not exceed the capacity of the vehicle. The most effective solution method proposed to date for this problem is due to Kohl, Desrosiers, Madsen, Solomon, and Soumis. Their algorithm uses a cutting-plane approach followed by a branchand -bound search with column generation, where the columns of the LP relaxation represent routes of individual vehicles. We describe a new implementation of their method, using Karger's randomized minimum-cut algorithm to generate cutting planes. The standard benchmark in this area is a set of 87 problem instances generated in 1984 by M. Solomon; making using of parallel processing in both the cutting-pla...

the last decade or so, exchange rate economics has seen a number of important developments, with substantial contributions to both the theory and the empirical understanding of exchange rate determination. Important developments in econometrics and the increasing availability of high-quality data have also stimulated a large amount of empirical work on exchange rates. While this research has improved our understanding of exchange rates, a number of challenges and questions remain. One of the most widely studied and still unanswered questions in this literature involves why monetary models of exchange rate determination cannot forecast much of the variation in exchange rates. The monetary approach to exchange rate determination emerged as the dominant exchange rate model at the outset of the recent float in the early 1970s and remains an important exchange rate paradigm (Frenkel, 1976; Mussa, 1976, 1979; Bilson, 1978). However, Meese and Rogoff’s (1983a) finding that monetary models ’ forecasts could not outperform a simple no-change forecast was a devastating critique of standard models and marked a watershed in exchange rate economics. Moreover, even with the benefit of 20 years of hindsight, evidence that monetary models can consistently and significantly outperform a naïve random walk is still elusive (e.g., see Mark and Sul, 2001; Rapach and Wohar, 2001a, 2001b; Faust, Rogers, and Wright, 2001). This article reviews this puzzle and discusses several potential explanations for the consistent failure of monetary models to forecast much variation in nominal exchange rates. We present the essential elements of the monetary model in the