Testing Part of a DSGE Model by Indirect Inference

We propose a way of testing a subset of equations of a DSGE model. The test draws on statistical inference for limited information models and the use of indirect inference to test DSGE models. Using the numerical small sample distribution of our test for two subsets of equations of the Smets–Wouters model we show that the test has accurate size and good power in small samples, and better power than using asymptotic distribution theory. In a test of the Smets–Wouters model on US Great Moderation data, we reject the specification of the wage‐price but not the expenditure sector. This points to the wage‐price sector as the source of overall model rejection.     

Preventives Versus Treatments Redux: Tighter Bounds on Distortions in Innovation Incentives with an Application to the Global Demand for HIV Pharmaceuticals

Kremer and Snyder (Q J Econ 130:1167–1239, 2015) show that demand curves for a preventive and treatment may have different shapes though they target the same disease, biasing the pharmaceutical manufacturer toward developing the lucrative rather than the socially desirable product. This paper tightens the theoretical bounds on the potential deadweight loss from such biases. Using a calibration of the global demand for HIV pharmaceuticals, we demonstrate the dramatically sharper analysis achievable with the new bounds, allowing us to pinpoint potential deadweight loss at 62% of the global gain from curing HIV. We use the calibration to perform policy counterfactuals, assessing welfare effects of government policies such as a subsidy, reference pricing, and price-discrimination ban. The fit of our calibration is good: we find that a hypothetical drug monopolist would price an HIV drug so high that only 4% of the infected population worldwide would purchase, matching actual drug prices and quantities in the early 2000s before subsidies in low-income countries ramped up.     

It is not just about paying your dues: Impact of generational cohort on active and passive union participation

The lack of a validated measure of active–passive union participation and a dearth of research into the relationship between generational cohort and union participation challenge union leaders to develop policies and practices to facilitate union renewal. We address these issues by (a) developing a multidimensional measure of union participation that captures both active and passive components, (b) using structural equation modelling to validate the measure within a nomological framework, and (c) investigating the impact of generational cohort on all paths in our framework. Data from members of a large American union confirm that generational cohort influences how union members participate in their union. The two‐factor measure developed in this study facilitates research into antecedents and outcomes of passive and active union participation. Our findings should also prove useful to unions seeking to increase participation within their membership, academics researching unions and generational cohort, and human resource practitioners operating in unionised environments.     

Alternative balanced scorecards built from paradigm models in strategic HRM and employment/industrial relations and used to measure the state of employment relations and HR system performance across U.S. workplaces

This paper constructs alternative balanced scorecards based on high‐performance work system (HPWS) and employment relations system (ERS) models. The models are depicted and compared in diagrams and used as framework skeletons for building separate HPWS and ERS scorecards, intended to provide a detailed data picture of the operational health and performance of an organization's employment/HR system and its operations, processes, and inputs/outputs. The scorecards are filled in with nationally representative data from 2,000+ U.S. workplaces using more than 50 employment/HR indicators, as reported by separate panels of managers and employees. The indicators for each workplace are aggregated into an overall HR/employment system score, ranked from low‐to‐high, and graphed as frequency distributions. These distributions provide a unique snapshot picture of the mean and dispersion of the state of employment relations and HR system performance for companies across the United State. They also reveal that “models matter” since the HPWS and ERS scorecards provide distinctly different evaluation assessments.     

The acerbity of the social: how to include the social in governmental risk assessments

This paper addresses the expansion of risk practices through a case study of a government led project in Sweden purposed to develop a method to include social events in mandatory risk practices. Social heterogeneity was to be transformed into straightforward causality in order to turn the social into a manageable object. In this regard, the project was quite successful. By inviting social scientists into the process, otherwise often marginalized within risk practice, causality and quantifiable risk factors could be established and the model became a rigorous and legitimate scientific model. Although experts were granted significant autonomy and became experts far beyond their own area of expertise, the success of the model lies rather in allowing experts authority within confined boundaries. Grand narratives and critical perspectives are disregarded as too abstract and if social scientists are to infuse aspects of social critique they must adapt to these circumstances: they must become instrumentalists.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.     

Brexit: How Will UK Agriculture Fare?

There is little doubt that Brexit would have significant implications for UK agriculture, a sector with strong trade links to the EU and strong reliance on CAP income support. This article reports preliminary results from employing a Computable General Equilibrium Model, a Partial Equilibrium Model and Farm Level Models to explore selected trade and domestic policy scenarios post‐Brexit. These allow for the estimation of changes in producer prices, production and farm incomes against a baseline scenario of continued EU membership. Under a Free Trade Agreement with the EU, agricultural impacts are relatively modest. By contrast, unilateral removal of import tariffs has significant negative impacts on prices, production and incomes. Adoption of the EU's WTO tariff schedule for all imports favours net importers (e.g. dairy) and harms net exporters (e.g. sheep). Given the strong dependence of most UK farms on direct payments, their removal worsens negative impacts of new trade arrangements and offsets positive impacts. Impacts vary across different types and sizes of farm, but also regionally. However, the period of adjustment to new trade and domestic policy conditions may prove very challenging for a large number of farm businesses.     

Wie die Materialengpässe den Arbeitsmarkt treffen

Wirtschaftsdienst - Although industrial production in Germany picked up again significantly with the recovery from the Corona crisis, supply bottlenecks for raw materials and intermediate products...