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This paper presents an updated meta-analysis of the effect of currency unions on trade, focusing on the euro area. Using meta-regression methods such as the funnel asymmetry test, evidence for strong publication bias is found. The estimated underlying effect for currency unions other than the eurozone reaches more than 60%. However, according to the meta-regression analysis, the euro's trade promoting effect corrected for publication bias is insignificant. The Rose effect literature shows signs of the economics research cycle: reported t-statistic is a quadratic concave function of the publication year. Explanatory meta-regression (robust fixed effects and random effects), that can explain about 70% of the heterogeneity in the literature, suggests that results published by some authors might consistently differ from the mainstream output and that study outcomes are systematically dependent on study design (usage of panel data, short- or long-run nature, number of countries in the data set).

The objective of this paper is to empirically assess the recently introduced models of subsidy competition based on the classical oligopoly theories, using both cross-sectional and panel data. Three crucial scenarios (including coordination, weak competition, and fierce competition) are tested employing OLS, iteratively re-weighted least squares, fixed effects, and Blundell-Bond estimator. The results suggest that none of the scenarios can be strongly supportedalthough there is some weak support for cooperation, and thus that empirical evidence is not in accordance with the tested models. Further, it seems that by means of FDI incentives countries try to compensate foreign investors for high wages or low productivity of their citizens.

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The transmission of monetary policy to the economy is generally thought to have long and variable lags. In this paper we quantitatively review the modern literature on monetary transmission to provide stylized facts on the average lag length and the sources of variability. We collect 67 published studies and examine when prices bottom out after a monetary contraction. The average transmission lag is 29 months, and the maximum decrease in prices reaches 0.9% on average after a onepercentage-point hike in the policy rate. Transmission lags are longer in developed economies (25-50 months) than in transition economies (10-20 months). We find that the factor most effective in explaining this heterogeneity is financial development: greater financial development is associated with slower transmission. Our results also suggest that researchers who use monthly data instead of quarterly data report systematically faster transmission.

We construct and explore a new quarterly dataset covering crisis episodes in 40 developed countries over 1970–2010. First, we examine stylized facts of banking, debt, and currency crises. Banking turmoil was most frequent in developed economies. Using panel vector autoregression, we confirm that currency and debt crises are typically preceded by banking crises, but not vice versa. Banking crises are also the most costly in terms of the overall output loss, and output takes about six years to recover. Second, we try to identify early warning indicators of crises specific to developed economies, accounting for model uncertainty by means of Bayesian model averaging. Our results suggest that onsets of banking and currency crises tend to be preceded by booms in economic activity. In particular, we find that growth of domestic private credit, increasing FDI inflows, rising money market rates as well as increasing world GDP and inflation were common leading indicators of banking crises. Currency crisis onsets were typically preceded by rising money market rates, but also by worsening government balances and falling central bank reserves. Early warning indicators of debt crisis are difficult to uncover due to the low occurrence of such episodes in our dataset. Finally, employing a signaling approach we show that using a composite early warning index increases the usefulness of the model when compared to using the best single indicator (domestic private credit).

We search for early warning indicators that could indicate important risks in developed economies. We therefore examine which indicators are most useful in explaining costly macroeconomic developments following the occurrence of economic crises in EU and OECD countries between 1970 and 2010. To define our dependent variable, we bring together a (continuous) measure of crisis incidence, which combines the output and employment loss and the fiscal deficit into an index of real costs, with a (discrete) database of crisis occurrence. In contrast to recent studies, we explicitly take into account model uncertainty in two steps. First, for each potential leading indicator, we select the relevant prediction horizon by using panel vector autoregression. Second, we identify the most useful leading indicators with Bayesian model averaging. Our results suggest that domestic housing prices, share prices, and credit growth, and some global variables, such as private credit, are risk factors worth monitoring in developed economies.

We construct and explore a new quarterly dataset covering crisis episodes in 40 developed countries over 1970-2010. First, we examine stylized facts of banking, debt, and currency crises. Using panel vector autoregression, we confirm that currency and debt crises are typically preceded by banking crises, but not vice versa. Banking crises are also the most costly in terms of the overall output loss, and output takes about six years to recover. Second, we try to identify early warning indicators of crises specific to developed economies, accounting for model uncertainty by means of Bayesian model averaging. Our results suggest that onsets of banking and currency crises tend to be preceded by booms in economic activity. In particular, we find that growth of domestic private credit, increasing FDI inflows, rising money market rates as well as increasing world GDP and inflation were common leading indicators of banking crises. Currency crisis onsets were typically preceded by rising money market rates, but also by worsening government balances and falling central bank reserves. Early warning indicators of debt crises are difficult to uncover due to the low occurrence of such episodes in our dataset. Finally, employing a signaling approach we show that using a composite early warning index significantly increases the usefulness of the model when compared to using the best single indicator (domestic private credit).

We provide a critical review of the literature on early warning indicators of economics crises and propose methods to overcome several pitfalls of the previous contributions. We use a quarterly panel of 40 EU and OECD countries for the period 1970-2010. As the response variable, we construct a continuous index of crisis incidence capturing the real costs for the economy. As the potential warning indicators, we evaluate a wide range of variables, selected according to the previous literature and our own considerations. For each potential indicator we determine the optimal lead employing panel vector autoregression, then we select useful indicators employing Bayesian model averaging. We re-estimate the resulting specification by system GMM to account for potential endogeneity of some indicators. Subsequently, to allow for country heterogeneity, we evaluate the random coefficients estimator and illustrate the stability among endogenous clusters. Our results suggest that global variables rank among the most useful early warning indicators. In addition, housing prices emerge consistently as an important domestic source of risk.