"Aggregation Bias" DOES explain the PPP puzzle

This article summarizes our views on the role of an "aggregation bias" in explaining the PPP Puzzle, in response to the several papers recently written in reaction to our initial contribution. We discuss in particular the criticisms of Imbs, Mumtaz, Ravn and Rey (2002) presented in Chen and Engel (2005). We show that their contentions are based on: (i) analytical counter-examples which are not empirically relevant; (ii) simulation results minimizing the extent of "aggregation bias"; (iii) unfounded claims on the impact of measurement errors on our results; and (iv) problematic implementation of small-sample bias corrections. We conclude, as in our original paper, that "aggregation bias" goes a long way towards explaining the PPP puzzle

Pairwise tests of purchasing power parity

Given nominal exchange rates and price data on N + 1 countries indexed by i = 0,1,2,…, N, the standard procedure for testing purchasing power parity (PPP) is to apply unit root or stationarity tests to N real exchange rates all measured relative to a base country, 0, often taken to be the U.S. Such a procedure is sensitive to the choice of base country, ignores the information in all the other cross-rates and is subject to a high degree of cross-section dependence which has adverse effects on estimation and inference. In this article, we conduct a variety of unit root tests on all possible N(N + 1)/2 real rates between pairs of the N + 1 countries and estimate the proportion of the pairs that are stationary. This proportion can be consistently estimated even in the presence of cross-section dependence. We estimate this proportion using quarterly data on the real exchange rate for 50 countries over the period 1957-2001. The main substantive conclusion is that to reject the null of no adjustment to PPP requires sufficiently large disequilibria to move the real rate out of the band of inaction set by trade costs. In such cases, one can reject the null of no adjustment to PPP up to 90% of the time as compared to around 40% in the whole sample using a linear alternative and almost 60% using a nonlinear alternative

How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study

In this paper, we present the results of Monte Carlo simulations for two popular techniques of long-range correlations detection - classical and modified rescaled range analyses. A focus is put on an effect of different distributional properties on an ability of the methods to efficiently distinguish between short and long-term memory. To do so, we analyze the behavior of the estimators for independent, short-range dependent, and long-range dependent processes with innovations from 8 different distributions. We find that apart from a combination of very high levels of kurtosis and skewness, both estimators are quite robust to distributional properties. Importantly, we show that R/S is biased upwards (yet not strongly) for short-range dependent processes, while M-R/S is strongly biased downwards for long-range dependent processes regardless of the distribution of innovations.Comment: 15 pages, 6 table

Business cycles, international trade and capital flows: Evidence from Latin America

This paper adopts a flexible framework to assess both short- and long-run business cycle linkages between six Latin American (LA) countries and the four largest economies in the world (namely the US, the Euro area, Japan and China) over the period 1980:I-2011:IV. The result indicate that within the LA region there are considerable differences between countries, success stories coexisting with extremely vulnerable economies. They also show that the LA region as a whole is largely dependent on external developments, especially in the years after the great recession of 2008 and 2009. The trade channel appears to be the most important source of business cycle comovement, whilst capital flows are found to have a limited role, especially in the very short run

Finance, foreign (direct) investment, and the Dutch disease: the case of Colombia

In recent years Colombia has grown relatively rapidly, but it has been a biased growth. The energy sector (the locomotora minero-energetica, to use the rhetorical expression of President Juan Manuel Santos) grew much faster than the rest of the economy, while the manufacturing sector registered a negative rate of growth. These are classic symptoms of the well-known ‘Dutch disease’, but our purpose here is not to establish whether the Dutch disease exists or not, but rather to shed some light on the financial viability of several, simultaneous dynamics: (i) the existence of a traditional Dutch Disease being due to a large increase in mining exports and a significant exchange rate appreciation; (ii) a massive increase in foreign direct investment (FDI), particularly in the mining sector; (iii) a rather passive monetary policy, aimed at increasing purchasing power via exchange rate appreciation; (iv) more recently, a large distribution of dividends from Colombia to the rest of the world and the accumulation of mounting financial liabilities. The paper will show that these dynamics constitute a potential danger for the stability of the Colombian economy. Some policy recommendations are also discussed