Oxford Bulletin of Economics and Statistics

Publisher:: Wiley
Publication date:: 2021-02-01

ISBN:: 0305-9049

Issue Number

Latest documents

Variance Decomposition Analysis for Nonlinear Economic Models1
In this paper, we propose a new method called the total variance method and algorithms to compute and analyse variance decomposition for nonlinear economic models. We provide theoretical and empirical examples to compare our method with the only existing method called generalized forecast error variance decomposition (GFEVD). We find that the results from the two methods are different when shocks are multiplicative or interacted in nonlinear models. We recommend that when working with nonlinear models researchers should use the total variance method in order to see the importance of indirect variance contributions and to quantify correctly the relative variance contribution of each structural shock.
Testing the Technology of Human Capital Production: A General‐to‐Restricted Framework
Studies of childhood development have suggested human capital is accumulated in complex and nonlinear ways. Nonetheless, empirical analyses of this process often impose a linear functional form. This paper investigates which technology assumptions matter in quantitative models of human capital production. I propose a general‐to‐restricted procedure to test the production technology, placing constraints on a modified McCarthy function, from which transcendental, constant elasticity of substitution, log‐linear and linear models are obtained as special cases. Applying the procedure to data on child height from the Young Lives surveys, as well as cognitive skills, I find that the technology of human capital production is neither log‐linear nor linear‐in‐parameters; rather, past and present inputs act as complements. I recommend that maintained hypotheses underlying functional form choices should be tested on a routine basis.
The Impact of the 2008 Crisis on UK Prices: What We Can Learn from the CPI Microdata1
This paper takes the locally collected price quotes used to construct the CPI index in the UK for the period 1996–2013 and explores the impact of the Great Recession (2008‐9) on the pricing behaviour of firms. We develop a time series framework which captures the link between macroeconomic variables and the behaviour of prices in terms of the frequency of price change, the dispersion of price levels and the size, dispersion and kurtosis of price‐growth. We find strong evidence for inflation having an effect, but not output. The change in the behaviour of prices during the Great Recession is largely explained by the changes in inflation and VAT. Nevertheless, the magnitude of the inflation effect is sufficiently small that it need not influence monetary policy.
A Simple Estimator of Two‐Dimensional Copulas, with Applications1
Copulas are distributions with uniform marginals. Non‐parametric copula estimates may violate the uniformity condition in finite samples. We look at whether it is possible to obtain valid piecewise linear copula densities by triangulation. The copula property imposes strict constraints on design points, making an equi‐spaced grid a natural starting point. However, the mixed‐integer nature of the problem makes a pure triangulation approach impractical on fine grids. As an alternative, we study the ways of approximating copula densities with triangular functions which guarantees that the estimator is a valid copula density. The family of resulting estimators can be viewed as a non‐parametric MLE of B‐spline coefficients on possibly non‐equally spaced grids under simple linear constraints. As such, it can be easily solved using standard convex optimization tools and allows for a degree of localization. A simulation study shows an attractive performance of the estimator in small samples and compares it with some of the leading alternatives. We demonstrate empirical relevance of our approach using three applications. In the first application, we investigate how the body mass index of children depends on that of parents. In the second application, we construct a bivariate copula underlying the Gibson paradox from macroeconomics. In the third application, we show the benefit of using our approach in testing the null of independence against the alternative of an arbitrary dependence pattern.
Gains from Wage Flexibility and the Zero Lower Bound*
We analyse the welfare impact of greater wage flexibility in the presence of an occasionally binding zero lower bound (ZLB) constraint on the nominal interest rate. We show that the ZLB constraint generally amplifies the adverse effects of greater wage flexibility on welfare when the central bank follows a conventional Taylor rule. When demand shocks are the driving force, the ZLB implies that an increase in wage flexibility reduces welfare even under the optimal monetary policy with commitment.
The Government Spending Multiplier at the Zero Lower Bound: Evidence from the United States
We estimate state‐dependent government spending multipliers for the United States. We use a factor‐augmented interacted vector autoregression (FAIVAR) model. This allows us to capture the time‐varying monetary policy characteristics including the recent zero interest rate lower bound (ZLB) state, to account for the state of the business cycle and to address the limited information problem typically inherent in VARs. We identify government spending shocks by sign restrictions and use a government spending growth forecast series to account for the effects of anticipated fiscal policy. In our baseline specification, we find that government spending multipliers in a recession range from 3.56 to 3.79 at the ZLB. Away from the ZLB, multipliers in recessions range from 2.31 to 3.05. Several robustness analyses confirm that multipliers are higher, when the interest rate is lower and that multipliers in recessions exceed multipliers in expansions. Our results are consistent with theories that predict larger multipliers at the ZLB.
The Individual Poverty Incidence of Growth
The canonical approach to analyse the poverty impact of growth is based on the comparison of poverty before and after growth. Measurement tools endorsing this approach fail to capture the different experiences of poverty dynamic in the population: there can be groups of the population made poorer or non‐poor made poor by growth. We propose an approach that allows measuring this individual poverty incidence of growth and show how it is related with existing models. We apply our framework to evaluate the poverty impact of growth in Indonesia, by comparing the 1993–2000 with the 2000–07 and 2007–14 growth spells.
Modelling Category Inflation with Multiple Inflation Processes: Estimation, Specification and Testing1
Zero‐inflated ordered probit (ZIOP) and middle‐inflated ordered probit (MIOP) models are finding increasing favour in the discrete choice literature. We propose generalizations to these models – which collapse to their ZIOP/MIOP counterparts under a set of simple parameter restrictions – with respect to the inflation process. These generalizations form the basis of a new specification test of the inflation process in ZIOP and MIOP models. Support for our generalization framework is principally demonstrated by revisiting a key ZIOP application from the economics literature, and reinforced by the reassessment of an important MIOP application from political science. Our specification test supports the generalized models over the original ZIOP/MIOP ones, suggesting an important role for it in modelling zero‐ and middle‐inflation processes.
Issue Information
Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing1
This paper stresses the bimodality of the likelihood function of the Mixed causal–noncausal AutoRegressions (MAR), and it is shown that the bimodality issue becomes more salient as the causal root approaches unity from below. The consequences are important as the roots of the local maxima are typically interchanged, attributing the noncausal component to the causal one and vice‐versa. This severely changes the interpretation of the results, and the properties of unit root tests of the backward root are adversely affected. To circumvent the bimodality issue, this paper proposes an estimation strategy which (i) increases noticeably the probability of attaining the global MLE; and (ii) selects carefully the maximum used for the unit root test against a MAR stationary alternative.