This note introduces the GGDC/UNU-WIDER Economic Transformation Database (ETD), which provides time series of employment and real and nominal value added by 12 sectors in 51 countries for the period 1990–2018. The ETD includes 20 Asian, 9 Latin American, 4 Middle-East and North African, and 18 sub-Saharan African countries at varying levels of economic development. The ETD is constructed on the basis of an in-depth investigation of the availability and usability of statistical sources on a country-by-country basis. The ETD provides researchers with data to analyse the variety and determinants of structural transformation and supports policies aimed at sustained growth and poverty reduction.

This study investigates excessive movements in capital flows called surges or bonanzas. Contrary to the previous work that extensively uses ad‐hoc measures and discretionary thresholds; we adopt a distinctive methodology to detect capital flow surges based on right‐tailed unit root tests. Generalized supremum augmented Dickey‐Fuller (GSADF) proposed by Phillips et al. (2015) is successfully applied to identify asset price bubbles. Exploiting the technical and conceptual similarities in the formations of asset price bubbles and capital flow surges, we perform the GSADF procedure using quarterly net capital flows data from 43 developing countries. The advantages of this procedure are twofold: it can distinguish the behaviour of volatility and explosiveness and diagnose multiple surges in a series. We identified 727 individual surges, 130 different surge episodes, and 4 global capital flow waves over the periods of 1995–2017. Compared with the existing measures, the application of this surge‐detection technique provides a useful tool as a data‐driven method with no need for discretionary thresholds. We also investigate the factors triggering capital flow surges, employing the Fernandez‐Val and Weidner (2016) bias‐adjusted fixed effects probit model and find that domestic factors play a dominant role on the surge occurrences in developing countries.

In this study, the effect of real exchange rate on bilateral trade balance between Turkey and its 25 main trade partners is investigated for the period of 1996-2015 with heterogeneous panel data techniques. Trade balance model is estimated by using Mean Group (MG) estimator, which allows parameter heterogeneity, Common Correlated Effects Mean Group (CCEMG), and Augmented Mean Group (AMG) estimators, which both allow cross-section dependency and heterogeneity. Results indicate that the real exchange rate elasticity of the trade balance ranges between-0.40 and-0.45 and Marshall-Lerner (ML) condition is valid for Turkey. According to the results, the foreign income elasticity of trade balance ranges between 1.54 and 2.84, while for domestic income elasticity, it is found between-0.75 and-1.38. Country-specific results show that ML condition is valid for the USA,

This study analyzes the role of push–pull factors on the level, volatility and comovement of capital flows in emerging markets (EMs). Taking the commonality of capital flows into account, we employ the panel Generalized Autoregressive Conditional Heteroscedasticity model developed by Cermeño and Grier for 16 EMs. This method not only accounts for country‐specific heterogeneity and cross‐section dependence but also allows the examination of the sources of the level, volatility and comovement of capital flows in a single step. The results show that domestic factors explain two‐thirds of the variation in net capital‐flow volatility. While both global and domestic factors, with the prominent ones being global risks and domestic economic growth, influence the comovement, their impacts somewhat vary by the types of capital flows.