Oxford Bulletin of Economics and Statistics最新文献

This paper uses OECD data to examine whether winning the men's FIFA World Cup boosts GDP growth, as claimed by analysts and media outlets concomitantly with every edition of this football competition. By implementing both an event-study design and a synthetic difference-in-difference strategy, the analysis shows that winning the World Cup increases year-over-year GDP growth by at least 0.48 percentage points in the two subsequent quarters. This result seems primarily driven by enhanced export growth, which is consistent with a greater appeal enjoyed by national products and services on the global market after victory in a major sporting event.

The consumption carbon intensity – defined as the carbon emissions per unit of consumption – varies with age: it is hump-shaped over the life cycle, but becomes flatter at high levels of income. We document this novel fact using US household-level consumption data. This relationship holds not only at the individual level, but also at the aggregate: we leverage information across US states and countries all around the world to show that the carbon intensity of the economy depends on the population age structure. Consequently, policy changes that alter carbon prices affect relatively more middle-age individuals, and especially so in low-income economies.

We forecast US inflation with a new Keynesian Phillips curve (NKPC) in the frequency domain. Our method consists of decomposing the time series of inflation and its NKPC predictors into several frequency bands, forecasting separately each frequency component of inflation, and then summing up those forecasts to obtain the forecast for aggregate inflation. We find that (i) accurately forecasting the low frequency of inflation is, on average, crucial to successfully forecast inflation; (ii) our NKPC low-frequency forecast model consistently and significantly outperforms the time-series NKPC and standard benchmark models; (iii) the low frequencies of inflation expectations and unemployment are the key predictors; and (iv) optimally switching on / off the forecasts of each frequency components of inflation at each period allows to outstandingly track inflation and show that all frequencies of inflation matter.

Standard recession forecasting based on economic indicators has become unsettled due to COVID-19 pandemic's limited but influential data. This paper proposes a new non-parametric approach to computing predictive probabilities of future recessions that is robust to influential observations and other data irregularities. The method simulates forecasts using past data histories embedded into a symbolic space. Then, the forecasts are converted into probability statements, which are weighted by the forecast probabilities of their respective symbols. Using GDP data from G7, our proposal outperforms other parametric approaches in classifying future national business cycle phases, especially including data from 2020 in the sample.

In this paper, a factor-augmented version of the New Keynesian Phillips curve (NKPC) is assessed using a data set comprised of a large panel of European Union (EU) member countries. The factor-augmentation is natural given that country-level inflation rates are highly co-moving. The presence of unattended common factors is important because it raises the issue of omitted variables bias, as the real marginal cost, which is a regressor of the NKPC, is likely to load on the same factors as inflation. One possibility here is to employ the regular instrumental variables approach. However, if the external instruments load on the same factors as the error term of the NKPC, the instruments would be invalid and the results would therefore likely be misleading. Motivated by this last observation, the present paper proposes a new estimator of the NKPC that allows for very general forms of factor dependencies and endogeneity. Our results provide evidence in support of the NKPC, but only after the presence of common factors has been appropriately accounted for.

The UK relationship between nominal wage inflation and the unemployment rate is unstable. Over sub-periods of the last 160 years of turbulent data, Phillips curve slopes range from strongly negative, slightly negative, flat, slightly positive and strongly positive. Our constant-parameter congruent model of real wages explains these instabilities, yet also implies a constant negative relationship between nominal wage inflation and the unemployment rate when corrected by its regressors. Disentangling these effects reveals that structural breaks in the real-wage model's variables do not explain the instabilities, which instead occur during sub-periods when some of its explanatory variables are insignificant.

We explore the demand for financial advice and the role of such advice in shaping household financial portfolios. Since taking financial advice may not be randomly allocated among households, understanding the drivers behind receiving financial advice is important before exploring the role of financial advice in shaping the composition of household portfolios. A number of specification tests are undertaken, including exploring the sensitivity of the results to selection as well matching estimation techniques. The analysis reveals that financial advice is inversely (positively) associated with the share of wealth held in real estate (bonds and stocks).

A society in which everybody of a given age has the same income will exhibit substantial income and wealth inequality. We use this idea to empirically quantify inter-cohort inequality – the share of observed inequality attributable to life-cycle profiles of income and wealth – using data on male earnings and household wealth. We document that recent increases in income and wealth inequality in the USA and other developed countries are larger than observed rates would suggest due to favourable demographics. That is, while demographic change played a substantial role in the dynamics of income and wealth inequality until 1990, the stark increase in inequality in the USA and elsewhere ever since is despite not because of demographic change. Moreover, we show that there is important variation across countries in the level and trends in the extent of inequality that is due to lifecycle effects, and that taking this into account gives a more nuanced view of cross-country comparisons.

This paper proposes two averaging estimation methods to improve the finite-sample efficiency of the instrumental variables quantile regression (IVQR) estimator. I propose using the usual quantile regression for averaging to take advantage of cases when endogeneity is not too strong. I also propose using two-stage least squares to take advantage of cases when heterogeneity is not too strong. The first averaging method is to apply a recent proposal for GMM averaging to the IVQR model based on this proposed intuition. My implementation involves many computational considerations and builds on recent developments in the quantile literature. The second averaging method is a new bootstrap model averaging method that directly averages among IVQR, quantile regression, and two-stage least squares estimators. More specifically, I find the optimal weights from bootstrapped samples and then apply the bootstrap-optimal weights to the original sample. The bootstrap method is simpler to compute and generally performs better in simulations, but uniform dominance results have not been formally proved. Simulation results demonstrate that in the multiple-regressors/instruments case, both the GMM averaging and bootstrap estimators have uniformly smaller risk than the IVQR estimator across data-generating processes with a variety of combinations of different endogeneity levels and heterogeneity levels.

This paper demonstrates that the decline in routine occupations and concurrent rise in abstract occupations are largely due to workers changing jobs. The reduction in routine manual tasks is further explained by workers transitioning to unemployment or retirement. In contrast, the increase in non-routine manual occupations is primarily driven by the entry of young or unemployed individuals into the workforce. Plant closure information is used to identify involuntary job separations. These findings indicate that routine cognitive workers can adjust to smaller employment disruptions compared to routine manual workers among women. However, a contrasting pattern is observed for men.