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Informal work is a significant feature of labour markets in many developed countries, despite having unemployment protection (UP) programmes. We use a model of job search over the duration of unemployment to study how the structure of these programmes influences the incentive of the unemployed to engage in informal work while searching for formal jobs. Accounting for informality enables the model to jointly explain three known features on job search dynamics: a temporary re-employment spike, low search effort, and negative duration dependence. The quantitative analysis finds that both informality and unemployment can be reduced by redistributing (across either workers or programmes), rather than increasing, the overall UP budget.

We develop a regime switching vector autoregression where artificial neural networks drive time variation in the coefficients of the conditional mean of the endogenous variables and the variance covariance matrix of the disturbances. The model is equipped with a stability constraint to ensure non-explosive dynamics. As such, it is employable to account for nonlinearity in macroeconomic dynamics not only during typical business cycles but also in a wide range of extreme events, like deep recessions and strong expansions. The methodology is put to the test using aggregate data for the United States that include the abnormal realizations during the recent Covid-19 pandemic. The model delivers plausible and stable structural inference, and accurate out-of-sample forecasts. This performance compares favourably against a number of alternative methodologies recently proposed to deal with large outliers in macroeconomic data caused by the pandemic.

This paper studies optimal macroeconomic policy when nonlinearity in the business cycle is described by a vector smooth transition autoregression (VSTAR). A structural identification of the VSTAR that yields a low-dimension and certainty-equivalent nonlinear quadratic regulator (NLQR) problem is derived. Optimal rules are calculated by adapting from the engineering theory the approach of State Dependent Riccati Equation, which allows standard dynamic programming techniques to solve NLQR problems. The methodology is employed to study optimal conventional and quantitative easing (QE) monetary policy using a VSTAR model esti-mated on data for the United States during 1979-2018. The model allows for regime changes during periods of economic slack and when interest rates are near the zero lower bound. The results highlight the quantitative significance of nonlinearity in the analysis of optimal monetary policy and how the size, timing and composition of QE can influence macroeconomic dynamics.

We study the sustainability of pension systems using a life-cycle model with distortionary taxation that sets an upper limit to the real value of tax revenues. This limit implies an endogenous threshold dependency ratio, i.e. a point in the cross-section distribution of the population beyond which tax revenues can no longer sustain the planned level of transfers to retirees. We quantify the threshold using a computable life-cycle model calibrated on the United States and fourteen European countries which have dependency ratios among the highest in the world. We examine the effects on the threshold and welfare of a number of policies often advocated to improve the sustainability of pension systems. New tax data on dynamic Laffer effects are provided.

This paper investigates the incentives that may induce workers to supplement income from unemployment benefits by engaging in temporary informal work. Using a dynamic model of job-search with moral hazard that incorporates a stylised schedule of benefit payments, we describe how informal sector participation changes over the duration of unemployment, in turn affecting the incentive to search for formal employment. We find that increasing benefit generosity makes job seekers less reliant on informal work, enabling them to search more intensively. At the same time, when detection rates are low, informal work participation may decline as benefit exhaustion approaches, reinforcing this effect. From a policy perspective, the analysis identifies scope for reallocation of resources towards less generous programmes within unemployment protection, which would reduce the size of the informal sector and unemployment in the economy.

This paper analyses the implications of heteroscedasticity for optimal macroeconomic policy and welfare. We find that changes in the variance structure driven by exogenous processes like generalized autoregressive conditional heteroscedasticity (GARCH) affect welfare but not the optimal feedback rule. However, changes in the variance structure driven by state-dependent processes affect both. We also derive certainty-equivalent transformations of state-dependent volatility models that allow standard quadratic dynamic programming algorithms to be employed to study optimal policy. These results are illustrated numerically using a reduced-form model of the US economy in which changes in volatility are driven by a GARCH process and the rate of inflation. Copyright © 2015 John Wiley & Sons, Ltd.

Recent evidence questions the nature of the re-employment spike as unemployment insurance (UI) payments expire. Unemployed agents do not appear to devote more time to search and are observed leaving the UI scheme early without necessarily entering employment. We show that benefit fraud is consistent with both observations. Over time, UI recipients become increasingly willing to accept short-term cash-in-hand work. This takes them away from job search. Immediately before UI expiry, the risk of punishment for fraud exceeds the value of remaining payments. Recipients may voluntarily leave the scheme to accept cash-in-hand opportunities.

Recent evidence questions the nature of the re-employment spike as unemployment insurance (UI) payments expire. Unemployed agents do not appear to devote more time to search and are observed leaving the UI scheme early without necessarily entering employment. We show that benefit fraud is consistent with both observations. Over time, UI recipients become increasingly willing to accept short-term cash-in-hand work. This takes them away from job search. Im- mediately before UI expiry, the risk of punishment for fraud exceeds the value of remaining payments. Recipients may voluntarily leave the scheme to accept cash-in-hand opportunities.