Foreign direct investment and technical progress in Spanish manufacturing

This article analyses the effects of Foreign Direct Investment (FDI) on technical progress in Spanish manufacturing. Particularly, we study how FDI's contributions vary depending on the economic structure of the industry. The results show that most FDI goes to capital-intensive sectors, especially when those sectors are also Research and Development (R&D)-intensive. Our estimates of the Solow residual show that the positive effect of contemporaneous and lagged FDI on manufacturing productivity is only attributable to capital and R&D intensive industries in what seems to be related to a dynamic capabilities explanation or to complementarities with R&D expenditures.     

Real exchange rate behavior

Using random simulations with artificial data with identical sample characteristics to the long-sample exchange rate data employed by Lothian and Taylor (Lothian, J.R. and Taylor, M.P. (1996). The recent float from the perspective of the past two centuries. Journal of Political Economy 104, 488–509.), we show that standard unit-root tests have extremely low power over sample sizes corresponding to the recent float. The probability of rejecting the null hypothesis when it is false is extremely low with 20 years or even 50 years of data and only reaches an acceptable level over much longer spans.     

Spatial econometric Monte Carlo studies: raising the bar

We discuss Monte Carlo methodology that can be used to explore alternative approaches to estimating spatial regression models. Our focus is on models that include spatial lags of the dependent variable, e.g., the SAR specification. A major point is that practitioners rely on scalar summary measures of direct and indirect effects estimates to interpret the impact of changes in explanatory variables on the dependent variable of interest. We argue that these should be the focus of Monte Carlo experiments. Since effects estimates reflect a nonlinear function of both \(\beta \) and \(\rho \), past studies’ focus exclusively on \(\beta \) and \(\rho \) parameter estimates may not provide useful information regarding statistical properties of effects estimates produced by alternative estimators. Since effects estimates have recently become the focus of inference regarding the significance of (scalar summary) direct and indirect impacts arising from changes in the explanatory variables, empirical measures of dispersion produced by simulating draws from the (estimated) variance–covariance matrix of the parameters \(\beta \) and \(\rho \) should be part of the Monte Carlo study. An implication is that differences in the quality of estimated variance–covariance matrices arising from alternative estimators also plays a role in determining the accuracy of inference. An applied illustration is used to demonstrate how these issues can impact conclusions regarding the performance of alternative estimators.     

Optimal Fiscal Policy in a Multisector Model: The Price Consequences of Government Spending

This paper investigates optimal fiscal policy in a static multisector model. A Ramsey type planner chooses tax rates on each good type as well as spending levels on each good type subject to an exogenous total expenditure constraint. It is shown that, like taxes, government spending policy has price effects and that these price effects have significant implications for optimal policy. These price effects imply a U shape to the government's objective function and this U shape results in boundary values for the choice of the spending allocation. In particular, it is shown that the optimal allocation of government spending tends to be concentrated on one good rather than spread among many goods.     

Technology-forcing through environmental regulation

This paper analyzes the demand characteristics of innovation in pollution abatement and the interaction between a regulator and a polluter under a technology-forcing policy. Important demand-driven determinants of innovation in pollution control are examined, such as uncertainties surrounding unexplored technologies, the length of the compliance period and the maximum abatement costs the regulator is willing to accept. We derive the formal condition that the regulator balances the marginal utility of emissions reduction against the marginal disutilities of a longer compliance time and the increased uncertainty about the feasibility of a more stringent standard.     

Patterns of poverty among elderly Americans: a latent class Markov model

This article studies poverty persistence and the role of social security programmes on poverty among elderly in the US. We use a Latent Markov model to disentangle unobserved heterogeneity and state dependence. Because of its dynamic nature, unobserved heterogeneity is modelled to vary over time. This allows to capture different latent states of poverty that change over time. Result indicates the existence of three unobserved types evolving over time according to their propensity to be poor. Moreover, a strong persistence in poverty especially for women, individuals living alone and ethnic minorities is found. Finally, the estimates indicate that giving social assistance tends to reduce poverty.     

Price Changes and Some Underlying Aspects of Measurement of Poverty

The paper deals with effects of price changes on measurement of poverty. It is shown that there are situations, when prices and nominal incomes change, a higher nutritional intake or an increase in commodity consumption of the poor can be associated with higher poverty gaps and a higher poverty index of the society. A positive relationship of this kind is quite counter-intuitive in the context of poverty measurement. This is caused by the adjustment of the poverty line and/or incomes of one situation by the prices of the other for the purpose of comparison.