Oxford Bulletin of Economics and Statistics最新文献

The Phillips curve began life in 1958 as a simple curve-fitted relationship between the rates of wage inflation and unemployment and went on to play a crucial role in the broader development of macroeconomics, giving rise to several controversies about its interpretation and role in policy-making. Recently, the traditional narrative about its theoretical underpinnings has been called into question as a sequence of ‘stories’ to provide support for particular theoretical perspectives on macroeconomics. The primary aim of this paper is to challenge the conventional wisdom relating to the Phillips curve being an attested empirical relationship, by showing that the empirical evidence of the most influential papers that helped to frame the traditional narrative is untrustworthy, in the sense that the probabilistic assumptions invoked by their inferences are invalid. That is, not only the traditional theory-driven narrative is misleading, but the empirical evidence used to corroborate it is untrustworthy.

Implementation lags are a concern of policymakers as they may reduce the efficacy of fiscal policy. Using a standard New Keynesian model with an effective lower bound on the nominal interest rate, we compare the impacts of fiscal stimulus on output across various lengths of implementation lag. We show that despite concerns among policymakers, implementation lags may enhance the efficacy of government purchases on output when the economy is caught in a liquidity trap.

Multivariate analysis can help to focus on important phenomena, including trend and cyclical movements, but any economic information in seasonality is typically ignored. The present paper aims to more fully exploit time series information through a multivariate unobserved component model for quarterly data that exhibits seasonality together with cross-variable component correlations. We show that economic restrictions, including common trends, common cycles and common seasonals can aid identification. The approach is illustrated using Italian GDP and consumption data.

How do government counterinsurgency efforts affect local public health financing during civil conflicts? We investigate this question in the context of the protracted conflict in Colombia. Using data on antinarcotics operations and health transfers from the central government to municipal governments, we employ both panel estimations and an instrumental variable to address concerns of endogeneity. We first show evidence of a government discretionary power over the allocation of health transfers. We do not find evidence that counterinsurgency operations causally affect health transfers to municipalities. Our results rule out political alignment between mayors and the national governing party as an intermediary factor that could influence the flow of fiscal transfers in municipalities exposed to the conflict.

Boom-and-bust cycles in the housing market pose a threat to macroeconomic and financial stability, thus calling for a timely assessment of imbalances. This work sheds light on the drivers of house price dynamics in some euro area economies, investigating the risks of overheating. We show that an Error-Correction-Model (ECM) featuring a long-run relationship between house prices and income and short-run effects of interest rates and housing supply fits the data well in most cases. We then propose a novel model-based misalignment indicator and find that extrapolative house price expectations play an important role in the build-up of speculative bubbles.

This paper investigates the causal effects of grandmothers' geographical proximity on labour supply decisions of married women with young children by leveraging a novel data set from Turkey. We deal with the reverse causality and endogeneity problems arising from mothers' and grandmothers' joint location and labour supply decisions by implementing a two-stage least squares estimation method using the number of alive grandmothers as an instrument. We argue that grandmothers' proximity can increase mothers' labour supply through their free and flexible childcare services. On the other hand, geographically close grandmothers can reduce mothers' labour supply by imposing the traditional gender norms prevalent in Turkey or requiring them to take on elderly caregiving duties. The overall effect depends on the relative size of these opposing factors. Our findings suggest that living in the same neighbourhood as grandmothers increases the probability of labour force participation and the employment rates of women with young children by 18.2 ppt and 16.4 ppt, respectively. These results are mostly driven by the non-village sample. The ‘traditional gender norm’ channel explains the insignificant impact of grandmothers' proximity on the labour market outcomes of mothers who have been raised in villages.

We illustrate the use of Pearl's (1995) front-door criterion with observational data with an application in which the assumptions for point identification hold. For identification, the front-door criterion leverages exogenous mediator variables on the causal path. After a preliminary discussion of the identification assumptions behind and the estimation framework used for the front-door criterion, we present an empirical application. In our application, we look at the effect of deciding to share an Uber or Lyft ride on tipping by exploiting the algorithm-driven exogenous variation in whether one actually shares a ride conditional on authorizing sharing, the full fare paid, and origin–destination fixed effects interacted with two-hour interval fixed effects. We find that most of the observed negative relationship between choosing to share a ride and tipping is driven by customer selection into sharing rather than by sharing itself. In the Appendix, we explore the consequences of violating the identification assumptions for the front-door criterion.

This paper presents a sample selection model with spatial correlation in the selection and outcome variables and studies the maximum likelihood method of estimation. Consistency and asymptotic normality of the maximum likelihood estimator are established by the spatial near-epoch dependent properties of the variables. Monte Carlo simulations show its good finite-sample performance. This model is used to examine the impact of climate change on cereal yields in Southeast Asia and projects that climate change may cause a reduction in cereal yields by $��7�\%�$ ($��31�\%�$) in the minimum-change (maximum-change) scenario.

I study the impact of stress resulting from the unexpected death of a child on parents' mortality risk. Using a flexible approach and allowing for time-varying treatment effects, I find no impact on the short-run mortality risk. However, I estimate a substantial increase in the long-run, particularly among men. I provide evidence that this group likely resorts to risky health behaviours such as heavy smoking and drinking as coping mechanisms. Assessing the possible protective effects of mental health support, I find evidence that it lowers the mortality risk for women. Mental health support has a smaller impact for men. I show that this is likely due to underutilization by those who would benefit the most. Finally, I present robustness of my results to specific departure from my identifying assumptions.

This paper examines the impact of environmental news coverage in US newspapers on stock markets. Using textual analysis with a dictionary-based approach, we obtain several measures of attention, tonality and uncertainty in the coverage of environmental news in major US newspapers. We consider different weighting schemes to account for the visibility and relevance of the text sources, and several sets of newspapers to measure the possible impact of their editorial line. Our results show that greater attention to environmental news in the US media reduced the excess returns of carbon-intensive stocks and increased their volatility over the last decade, especially when the coverage was uncertain. The opposite result holds for the most virtuous green assets. Restricting the corpus of texts to conservative newspapers mitigates the impact of coverage. Overall, our results illustrate how rising environmental concerns lead investors to change their asset allocation.