Catálogo de publicaciones - libros

In order to study rigorously the propagation of macroeconomic shocks, we construct a dynamic model with wage and price staggering, where wage and price contracts are set by fully maximizing agents in a framework of imperfect competition. We derive the optimal values for wage and price contracts and compute closed form solutions to the resulting dynamics. We show that wage and price contracts of reasonable durations can create persistence and a hump in the response of both output and inflation to monetary shocks.

We construct a one-sector growth model where the technology is described by a Variable Elasticity of Substitution (VES) production function. This framework allows the elasticity of factor substitution to interact with the level of economic development. First, we show that the model can exhibit unbounded endogenous growth despite the absence of exogenous technical change and the presence of non-reproducible factors. Second, we provide some empirical estimates of the elasticity of substitution, using a panel of 82 countries over a 28-year period, which admit the possibility of a VES aggregate production function with an elasticity of substitution that is greater than one and consequently of unbounded endogenous growth.

In this paper we examine the effect of financial development on economic growth in an additive Instrumental Variable (IV)-augmented Partially Linear Regression (PLR) model using panel data of 66 countries for the period 1961-1995. Three common measures of financial development are used. Our results show that the effect of the exogenous component of a financial intermediary development index on economic growth depends greatly on the definition and measurement of that index. Financial development affects growth in a positive but non-linear way using a Liquid Liabilities index and in an almost linear way when using a Private Credit index. The effect becomes ambiguous when a Commercial-Central Bank index is used.

The marked gap that exists between macroeconomic theory models and applied econometric findings arises because most observed data variability in macro-econometrics is due to factors that are absent from economic theories, but which econometric models have to tackle (particularly various non-stationarities). may be fine for theoretical reasoning, but is unacceptable for empirical modelling. A ‘minor influence’ theorem is needed instead which can only be established empirically. Thus, the chapter considers an automatic selection approach to bring objectivity and credibility to empirical econometric modelling.

This paper tests Mankiw’s [9] revenue-smoothing hypothesis, that the inflation rate moves one-for-one with the marginal tax rate in the long run, using the new average marginal tax rate series constructed by Stephenson [16] and the long-horizon regression approach developed by Fisher and Seater [5]. It reports considerable evidence against revenuesmoothing.

We examine the consequences of extracting structural shocks in VAR models using standard standard inertial restrictions, when the data has been generated by two stochastic dynamic general equilibrium (DSGE) models featuring different types of microfundations and different sources of sluggishness. We find that, in general, misspecification is substantial: short run coefficients often have wrong signs; impulse responses and variance decompositions give misleading representations of the dynamics; inexistent puzzles are created. We show that an omitted variables bias accounts for the results and propose an alternative identification technique which can cope with the inherent underidentification displayed by the DSGE models currently used in macroeconomics.

The Keynes-Einzig conjecture states that discrepancies between interest parities and forward rates in the interwar period did not cause deliberate transfers through interest arbitrage on a large scale unless and until the profit on the operation was at least 1/2 percent per anum. We further examine this conjecture by employing monthly data for six currencies against the US Dollar for the period 1921-1936. In particular, we analyse the real returns to uncovered forward speculation in the interwar period. We find that excess returns were predictable and that deviations from covered interest parity (CIP) were large and systematic. Evidence of nonlinear adjustment of CIP is also provided.

This paper investigates the relationship between the quarterly opinion poll lead of UK governments over the period 1955–1996, and a set of economic indicators. The hypothesis of a causal link between these variables is often debated, but there is a difficulty in testing the link by conventional econometric methods. These require either stationarity or the I(1) property, but there is strong evidence from a number of different studies that opinion poll series are fractionally integrated, being nonstationary but also mean-reverting.

This paper tests the hypothesis of fractional cointegration using bootstrap methods. It first discusses the problem of defining a cointegrating relationship between series that may not have the same order of integration, and suggests a generalized cointegration model that might account for this case. Bootstrap tests of the regular and generalized (non-)cointegration hypotheses are performed, as well as tests of the null hypothesis that cointegration of either type exists. Both the regular and double bootstrap statistics are calculated, the latter method providing a correction to the finite sample size distortion to the estimation of unknown parameters.

The tests reveal little or no evidence of a link between the political and economic cycles, a conclusion that reinforces the results of earlier work suggesting that the political cycle is generated by the internal dynamics of the opinion formation process. The findings are reinforced by a case-specific Monte Carlo study, showing that the methods have ample power to reveal cointegrating relations, if they exist.

This paper presents a selective survey of the literature on non-stationarity tests, namely standard and efficient unit root tests and stationarity tests, with or without structural changes. We also present the direct relation between non-stationarity tests and four economic theories, such as business cycles, hysteresis, purchasing power parity and convergence.

In this paper we focus on two STS models suitable for forecasting the index of industrial production. The first model requires that the index be transformed with a first and seasonal difference filters. The second model considers the index in its second difference filter, while seasonality is modeled with a constant and seasonal dummy variables. Tests designed to discriminate empirically between these two models are also conducted. Our results prefer the performance of the second model, particularly when the conventional ML estimation procedure is replaced by the ALS procedure. This process together with appropriate seasonal adjustment advances the possibility of using the suggested index forecasts to help to predict business cycle turning points.