We develop inference procedures robust to general forms of weak dependence. The procedures utilize test statistics constructed by resampling in a manner that does not depend on the unknown correlation structure of the data. We prove that the statistics are asymptotically normal under the weak requirement that the target parameter can be consistently estimated at the parametric rate. This holds for

This paper documents the determinants of real oil price in the global market based on an empirical model embedding transitory and permanent shocks. We find evidence of significant differences in the propagation mechanisms of transitory versus permanent disturbances, pointing to the importance of disentangling their distinct effects. Permanent supply shocks are found to be very influential in driving

We study the gains from using short-dated options for volatility measurement and forecasting. Using option portfolios, we estimate nonparametrically spot volatility under weak assumptions for the underlying asset. This volatility estimator complements existing ones constructed from high-frequency returns. We show empirically, using the market index and Dow 30 stocks, that combining optimally return

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP, consumption and investment growth, our results suggest that the news data contains information not captured

Financial bubbles arise when the underlying asset's market price deviates from its fundamental value. Unlike other bubble tests that use time series data and assume a reduced-form price process, we infer the existence of bubbles nonparametrically using option price data. Under no-arbitrage and acknowledging data constraints, we can partially identify asset price bubbles using a cross section of European

This paper provides new evidence on the cyclical behaviour of household labour income risk in Great Britain and the role of social insurance policy in mitigating against this source of income risk. To achieve this, we decompose stochastic idiosyncratic household income into its transitory and persistent components. We focus our analysis of income risk captured by the second to fourth moments of the

This paper revisits the well-known VAR evidence on the real effects of uncertainty shocks by Bloom (Econometrica 2009(3): 623-685. doi: 10.3982/ECTA6248). We replicate the results in a narrow sense using Eviews. In a wide sense, we extend his study by working with a smooth transition-VAR framework that allows for business cycle-dependent macroeconomic responses to an uncertainty shock. We find a significantly

This paper presents estimates of the economic effects of secession for a large panel of countries that gained independence between 1940 and 2016. It relies on a semi-parametric identification strategy that controls for the confounding effects of past GDP dynamics, anticipation effects, unobserved heterogeneity, model uncertainty and effect heterogeneity. Our findings indicate that secession lowered

We estimate a two-country model of the US and Canada over the post 2009 sample to study the cross-country spillovers of forward guidance shocks. To do so, we propose a method to identify forward guidance shocks during the fixed interest rate regime. The estimated forward guidance shocks coincide with significant US monetary policy announcements such as the introduction of calendar based guidance in

Chudik, Kapetanios, and Pesaran (Econometrica 2018, 86, 1479-1512) propose a one covariate at a time, multiple testing (OCMT) approach to variable selection in high-dimensional linear regression models as an alternative approach to penalised regression. We offer a narrow replication of their key OCMT results based on the Stata software instead of the original Matlab routines. Using the new user-written

Structural models that admit multiple reduced forms, such as game-theoretic models with multiple equilibria, pose challenges in practice, especially when parameters are set-identified and the identified set is large. In such cases, researchers often choose to focus on a particular subset of equilibria for counterfactual analysis, but this choice can be hard to justify. This paper shows that some parameter

Increased global integration of firm, production, and financial networks has the potential to benefit growth but also amplify the transmission of crises. We test whether higher global connectedness is associated with robust (beneficial) or fragile (harmful) behavior using networks derived from firm equity returns across all industries (1991-2016). More globally connected firms are less likely to be

The American Time Use Survey (ATUS) accurately measures hours worked on a single day. We propose several estimators of elasticities of weekly labor supply in a linear regression model, despite certain impossibility results due to the time specific feature of the ATUS. We recommend the impute estimator, a simple modification of the standard two stage least squares estimator, that imputes the dependent

We analyze the impact of choosing an elite school on high school graduation in an early tracking system in Flanders (Belgium). While elite schools offer only an academic track, most other schools offer multiple tracks. On average, students experience a 3.3 percentage point increase in the likelihood of obtaining a degree. We find that the effects are heterogeneous. On average, students who self-select

Induced sparsity in the factor loading matrix identifies the factor basis, while rotational identification is obtained ex-post by clustering methods closely related to machine learning. We extract meaningful economic concepts from a high-dimensional data set, which together with observed variables follow an unrestricted, reduced-form VAR process. Including a comprehensive set of economic concepts allows

We show that Bertrand et al.’s (QJE 2015) finding of a sharp drop in the relative income distribution within married couples at the point where wives start to earn more than their husbands is unstable across different estimation procedures and varies across contexts. We apply the estimators by McCrary (JoE, 2008, McC) and Cattaneo et al. (JASA, 2020, CJM) to administrative data from the US and Germany

This study replicates and challenges the finding of zero wage returns to compulsory schooling in Germany by Pischke and von Wachter (Review of Economics and Statistics, 90(3), 592-598), which is unusual in the literature yet widely cited and until now uncontradicted. I document that this finding is sensitive to minor changes in sample restrictions and model specification. Further results suggest that

Second-degree dominance has become a widely accepted criterion for ordering distribution functions according to social welfare. However, it provides only a partial ordering, and it may fail to rank distributions that intersect. To rank intersecting distribution functions, we propose a general approach based on rank-dependent theory. This approach avoids making arbitrary restrictions or parametric assumptions

The risk of AIDS-related mortality increased dramatically throughout the 1990s. This paper updates previous work by Fortson (2011) to examine the impact of mortality risk on human capital investment during the deadliest period of the pandemic. We combine Demographic Health Survey data from 30 countries, across 60 survey waves, to generate a sample of over 1,300,000 observations. Cohort-specific analysis

We introduce a new joint test for the order of fractional integration of a multivariate fractionally integrated vector autoregressive (FIVAR) time series based on applying the Lagrange multiplier principle to a feasible generalised least squares estimate of the FIVAR model obtained under the null hypothesis. A key feature of the test we propose is that it is constructed using a heteroskedasticity-robust

We use a Bayesian vector autoregression with stochastic volatility to forecast government bond yields. We form the conjugate prior from a no-arbitrage affine term structure model. The model improves on the accuracy of point and density forecasts from a no-change random walk and an affine term structure model with stochastic volatility. Our proposed approach may succeed by relaxing the no-arbitrage

We propose a methodology to classify individuals into few but meaningful health groups by estimating a panel Markov switching model that exploits rich information from panel household surveys. Using the HRS, we identify four persistent health groups, depending on individual's physical and mental disabilities. Our classification outperforms existing health measures at explaining entry in nursing homes

This paper investigates the potentials of the bootstrap as a tool for inference on the parameters of macroeconometric models which admit a state space representation. We consider a bootstrap estimator of the parameters of state space models and show that the bootstrap realizations of this estimator, usually employed to approximate asymptotic confidence intervals, p-values and critical values of tests

Change-point (CP) VAR models face a dimensionality curse due to the proliferation of parameters that arises when new breaks are detected. We introduce the Sparse CPVAR model which determines which parameters truly vary when a break is detected. By doing so, the number of new parameters to be estimated at each regime is drastically reduced and the break dynamics becomes easier to be interpreted. The

We propose a Release-Augmented Dynamic Factor Model (RA-DFM) that allows to quantify the role of a country's data flow in nowcasting both early GDP releases, and subsequent revisions of official estimates. We use the RA-DFM to study UK GDP early revision rounds, and assemble a comprehensive and novel mixed-frequency dataset that features 12 years of real-time data vintages. The RA-DFM improves over

Using a novel, nationally representative dataset containing the expectations of 380,000 Australians, individuals are shown to form expectations in a manner inadequately explained by popular expectation mechanisms. Approximately 1 in 5 individuals form inflation expectations that are negatively related to their own-income changes, even after accounting for their level of optimism regarding future economic

Point forecasts can be interpreted as functionals (i.e., point summaries) of predictive distributions. Considering situations where forecasters' preferences are unknown, we integrate and reinterpret existing, and develop new, methodology for the identification of the functional based on time series of point forecasts and associated realizations. Focusing on the natural cases of state-dependent quantiles

Based on linked administrative and survey panel data, we analyze the labour supply behaviour of physicians who could adopt either a standard fee-for-service contract or a mixed remuneration (MR) contract. Under MR, physicians received a per diem and a reduced fee for services provided. We present estimates of a structural discrete choice model that incorporates service intensity (services provided

This paper investigates productivity effects for a given firm resulting from the import or export of intermediate inputs by domestic upstream and downstream industries. Using manufacturing firms in 19 EU countries over the period 2000-2014, we find that domestic access to intermediate inputs that are also exported leads to higher levels of revenue productivity. The effect appears as more prominent

Oil traders find it challenging to process all information and choose which sources to follow. Inventories represent a perfect source, as they provide important information regarding real agents’ intertemporal decisions and can easily be observed in real time. However, inventories do not contain full information about the state of the oil market. We show that financial traders fail to acquire additional

Based on a large historical panel dataset, this paper provides evidence that the government spending multiplier can be significantly higher when interest rates are at or near the zero lower bound (ZLB). We estimate multipliers that are as high as 1.5 during ZLB episodes but small and statistically indistinguishable from zero during normal times. Our results are robust to different definitions of ZLB