Arne J. Nagengast

The Great Collapse in Value Added Trade

This paper studies the great collapse in value added trade using a structural decomposition analysis. We show that changes in vertical specialisation accounted for almost half of the great trade collapse, while the previous literature on gross trade has mainly focused on final expenditure, inventory adjustment and adverse credit supply conditions. The decline in international production sharing during the crisis may partially account for the observed decrease in global trade elasticities in recent years. Second, we find that the drop in the overall level of demand accounted for roughly a quarter of the decline in value added exports while just under one third was due to compositional changes in final demand. Finally, we demonstrate that the dichotomy between services and manufacturing sectors observed in gross exports during the great trade collapse is not apparent in value added trade data.

Accounting for the Differences Between Gross and Value Added Trade Balances

One of the main stylised facts that has emerged from the recent literature on global value chains is that bilateral trade imbalances in gross terms can differ substantially from those measured in value added terms. However, the factors underlying the extent and sign of the differences between the two measures have so far not been investigated. Here, we propose a novel decomposition of bilateral gross trade balances that accounts for the differences between gross and value added concepts. The bilateral analysis contributes conceptually to the literature on double counting in trade by identifying the trade flow in which value added is actually recorded for the first time in international trade statistics. We apply our decomposition framework to the development of intra‐EU‐27 trade balances from 1995 to 2011 and show that a growing share of intra‐EU bilateral trade balances is due to demand in countries other than the two direct trading partners. The latter accounted for 25 per cent of the total variance of intra‐EU gross bilateral trade balances in 2011, which marks a considerable rise from 3 per cent in 1995.

Productive capabilities: An empirical analysis of their drivers

Recent contributions to the growth and trade literature have argued that the structure of an economy, as measured by its productive capabilities, is a key determinant for inter-country differences in development. Productive capabilities have been shown to be highly predictive of future economic growth, yet the country-level variables associated with them remain relatively unknown. In this paper, we empirically explore what variables are systematically associated with productive capabilities using a model averaging framework that can handle a very large number of potential explanatory variables without the need for arbitrary model selection. In order to estimate our dynamic panel specification, we propose a novel Bayesian averaging of classical estimates procedure based on the simple and efficient bias-corrected least squares dummy variable estimator. Our baseline and robustness analysis consider a large number of variables, sample periods and model priors. We find that there is persistence (as measured by the lagged dependent variable) and that variables, such as commodity terms of trade, energy availability, government consumption, capital per worker, arable land and capital inflows show a strong and robust association with capabilities.