Oxford Bulletin of Economics and Statistics最新文献

We specify a multiple-equation model with equilibrium-correction terms, which connect inflation to the wage share and the functional income distribution, while not excluding a priori variables that are typically found in existing empirical U.S. Phillips curve models. We estimate the model equations using automatic variable selection with low Type-1 error probabilities on a sample with quarterly data that starts in the 1960s. Conditional on a relatively small number of location shift indicators, the price and wage equations have relatively constant parameters. The model's explanatory power is shown by dynamic simulations. Applied to the COVID-19 period, the model shows that wage growth was important initially but that other factors later also became important, in particular the broad increase in international prices. Out-of-sample simulation shows how well the model forecasts inflation since early 2023.

This study explores optimal monetary policy rules under commitment in a behavioural new Keynesian (NK) model. We show how the degree of cognitive discounting affects the properties of the optimal monetary policy rule. Our findings are summarised as follows. First, allowing predominant cognitive discounting may render the optimal rule ineffective because it is less likely to impart policy inertia into the economy. Second, despite the degree of nominal price stickiness, the costs of a discretionary policy can be relatively smaller in a behavioural NK model than in the standard NK model. Third, the degree of cognitive discounting influences the properties of optimal monetary policy rules under the zero lower bound on the nominal interest rate. Finally, the degree of interest rate stabilisation in the loss function is crucial in explaining the properties of optimal monetary policy in a behavioural NK model.

Estimates of poverty are an important input into policy formulation in developing countries, making the accurate measurement of poverty rates a first-order problem for development policy. This paper shows that combining satellite imagery with household surveys can improve the accuracy and precision of estimated poverty rates in Mexican municipalities, a level at which the survey is not considered representative. It also shows that empirical best prediction (EBP) based on a twofold household-level model outperforms EBPs based on other common small area estimation models. These results indicate that the incorporation of household survey data and widely available satellite imagery can improve poverty estimates in developing countries, even for small subgroups.

Time-varying coefficient models have drawn great attention in both theoretical and empirical research. This article introduces two consistent tests, based on a randomised procedure, to distinguish whether time-varying coefficients behave as deterministic functions of time or as unit root processes. By formulating the null hypothesis for each specification, we establish that the proposed test statistics asymptotically follow a chi-squared distribution under their respective null hypotheses and diverge to infinity in probability under their respective alternative hypotheses. Simulation studies demonstrate the satisfactory performance of both test statistics in finite samples. Furthermore, we apply the proposed tests to analyse various financial and macroeconomic datasets. The results of the tests reveal that deterministic functions of time should be adopted for these applications.

A testing principle is introduced where the statistic is the ratio of two weighted averages. The ratio converges to the standard Cauchy distribution under the null hypothesis. At the same time, a potential nuisance scaling parameter cancels from the ratio without having to be estimated, making these Cauchy tests self-normalising. These tests are not directed against specific alternatives and belong to the toolkit of general specification testing. We indicate how Cauchy tests can be extended to a multivariate framework of correlated samples, such that the tests are robust with respect to cross-dependence without the need to explicitly account for it.