Total Factor Productivity (TFP) accounts for a sizeable proportion of the income and growth differences across countries. Two challenges remain to researchers aiming to explain these differences: on the one hand, TFP growth is hard to measure; on the other hand, model uncertainty hampers...

In this paper, we consider a partially linear panel data model with cross-sectional dependence and non-stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence structure, we then establish...

This paper is concerned with the estimation of euro area potential output growth and its decomposition according to the sources of growth. The growth accounting exercise is based on a multivariate structural time series model which combines the decomposition of total output according to the...

An error-correction model identifies determinants of growth consistent with results from panel regressions based on a standard Cobb-Douglas production function for El Salvador for 1970-1995, with structural factors affecting the technology variable and macroeconomics and expectations explaining...

This paper investigates the nonlinearity in the effects of news shocks about technological innovations. In a maximally flexible logistic smooth transition vector autoregressive model, state-dependent effects of news shocks are identified based on medium-run restrictions. We propose a novel...

This paper evaluates the effects of the North American Free Trade Agreement on the economic growth of Mexico, the United States and Canada by means of an augmented Solow growth model. Such a model is estimated with panel data through two econometric methods: 1) the Arellano-Bond dynamic panel...

Machine Learning models are often considered to be "black boxes" that provide only little room for the incorporation of theory (cf. e.g. Mukherjee, 2017; Veltri, 2017). This article proposes so-called Dynamic Factor Trees (DFT) and Dynamic Factor Forests (DFF) for macroeconomic forecasting, which...

Technological change is modeled as endogenous in the sense that it is affected by economic, behavioral, and institutional variables. Technological change is especially affected by changes in relative input prices and their level, of which the price of labor is particularly important. Input...

We investigate the effects of political institutions on economic growth. We specifically explore this relationship while controlling for heterogeneity and model uncertainty. We use threshold regression (Hansen (2000)) to search for possible nonlinearities and/or interaction effects with respect...

This paper contributes to the productivity literature by using results from firm-level productivity studies to improve forecasts of macro-level productivity growth. The paper employs current research methods on estimating firm-level productivity to build times-series components that capture the...