Mr. Serhat Solmaz, Marzie Taheri Sanjani, and Mr. Vikram Haksar
External headwinds, together with domestic vulnerabilities, have loomed over the prospects of
emerging markets in recent years. We propose an empirical toolbox to quantify the impact of external
macro-financial shocks on domestic economies in parsimonious way. Our model is a Bayesian VAR
consisting of two blocks representing home and foreign factors, which is particularly useful for small
open economies. By exploiting the mixed-frequency nature of the model, we show how the toolbox
can be used for “nowcasting” the output growth. The conditional forecast results illustrate that regular
updates of external information, as well as domestic leading indicators, would significantly enhance
the accuracy of forecasts. Moreover, the analysis of variance decompositions shows that external
shocks are important drivers of the domestic business cycle.
Karim Barhoumi, Laurent Ferrara, and Joel Toujas-Bernate
This paper develops a new monthly World Trade Leading Indicator (WTLI) that relies on nonparametric and parametric approaches. Compared to the CPB World Trade Monitor’s benchmark indicator for global trade the WTLI captures turning points in global trade with an average lead between 2 and 3 months. We also show that this cyclical indicator is able to track the annual growth rate in global trade, suggesting that the recent slowdown is due in part to certain cyclical factors. This new tool can provide policy makers with valuable foresight into the future direction of economic activity by tracking world trade more efficiently.
Mr. Maxwell Opoku-Afari, Shiv Dixit, and Mr. Peter Allum
This paper uses a set of routinely collected high-frequency data in low-income countries (LICs) to construct an aggregate and a comprehensive index of economic activity which could serve (i) as a measure of the direction of economic activity; and (ii) as a useful input in analyzing contemporaneous real sector performance in LICs in the absence of high-frequency, and often outdated, GDP data. It could also serve as a useful tool for policymakers to gauge short-term dynamics of economic activity and shape appropriate and timely policy responses.
This study proposes a data-based algorithm to select a subset of indicators from a large data set with a focus on forecasting recessions. The algorithm selects leading indicators of recessions based on the forecast encompassing principle and combines the forecasts. An application to U.S. data shows that forecasts obtained from the algorithm are consistently among the best in a large comparative forecasting exercise at various forecasting horizons. In addition, the selected indicators are reasonable and consistent with the standard leading indicators followed by many observers of business cycles. The suggested algorithm has several advantages, including wide applicability and objective variable selection.
S. Borağan Aruoba, Francis X. Diebold, M. Ayhan Kose, and Marco E. Terrones
We propose and implement a framework for characterizing and monitoring the global business cycle. Our framework utilizes high-frequency data, allows us to account for a potentially large amount of missing observations, and is designed to facilitate the updating of global activity estimates as data are released and revisions become available. We apply the framework to the G-7 countries and study various aspects of national and global business cycles, obtaining three main results. First, our measure of the global business cycle, the common G-7 real activity factor, explains a significant amount of cross-country variation and tracks the major global cyclical events of the past forty years. Second, the common G-7 factor and the idiosyncratic country factors play different roles at different times in shaping national economic activity. Finally, the degree of G-7 business cycle synchronization among country factors has changed over time.
This paper proposes a new way of computing a coincident indicator for economic activity in France using data from business surveys. We use the generalized dynamic factor model à la Forni and others (2000) to extract common components from a large number of survey observations. The results obtained show that the resulting indicator forecasts economic activity with a relatively high degree of accuracy before the release of actual data.
The analysis of coincident and leading indicators can help policymakers gauge the short-term direction of economic activity. While such analysis is well established in advanced economies, it has received relatively little attention in many emerging market and developing economies, reflecting in part the lack of sufficient historical data to determine the reliability of these indicators. This paper presents an econometric approach to deriving composite indexes of coincident and leading indicators for a small open economy, Jordan. The results show that, even with limited monthly observations, it is possible to establish meaningful economic and statistically significant relations between indicators from different sectors of the economy and the present and future direction of economic activity.
This paper uses the classical (level) definition of business cycles to analyze the characteristics-duration, amplitude, steepness, and cumulative output movements-of the real GDP series of France, Germany, Italy, the rest of the euro area, and the United States. An index of concordance and its test statistic suggest a great deal of comovement/synchronization between output cycles. Following that result, a dynamic factor model is estimated. Output fluctuations are mostly explained by a global common component and an euro area common component. However, idiosyncratic components also matter, especially for France, the rest of the euro area, and the United States.
We use the regime-switching econometric models in Hamilton (1989) and Filardo (1994) to study business cycles in Mexico. In particular, we characterize the ups and downs of economic activity in Mexico. As a proxy for economic activity, we use the Mexican quarterly industrial production index from the second quarter of 1972 to the third quarter of 1999. We allow the transition probabilities driving changes in economic activity to be a function of fiscal, financial, and external sector indicators. Our results show that recessions in Mexico are deeper and shorter than expansions.
Time series on economic activity in developing countries, in particular real GDP, are reported with important lags. Therefore, it is useful to construct indicators that coincide or lead the actual direction and level of economic activity. A general methodology to construct these indicators is proposed and adapted for Argentina. Three coincident indicators could be constructed, but no reliable leading indicator could be found. From an econometric standpoint, the coincident indicators produce satisfactory point estimates of real GDP. The series that enter the indicator are broadly consistent with what many economists believe is the main source of real GDP fluctuations in Argentina: shocks to the capital account of the balance of payments. This enhances the confidence in the econometric results.