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1. Public and Private Pension Systems and Macroeconomic Volatility in OECD Countries

Author:
Mario Holzner, Stefan Jestl, and David Pichler
Publication Date:
12-2019
Content Type:
Working Paper
Institution:
The Vienna Institute for International Economic Studies (WIIW)
Abstract:
This paper analyses the impact of public pension expenditures and pension funds’ assets as well as their benefits on economic volatility. To do so, we use panel data for 35 OECD countries for the period 1980-2018 and apply a set of state-of-the-art econometric estimators. Our results show weak evidence of a negative impact of public pension expenditures as well as weak evidence of a positive impact of pension funds’ benefits on volatility. Results were, however, found not to be very robust. In contrast, pension funds’ assets do not show any evidence of being associated with economic volatility. Unsystematic fiscal policy, banking crises and political (in)stability, however, are revealed to be somewhat more robust determinants of economic volatility.
Topic:
Economics, Public Sector, Econometrics, and Organisation for Economic Co-operation and Development
Political Geography:
Global Focus

2. Outliers in semi-parametric Estimation of Treatment Effects

Author:
Darwin Ugarte Ontiveros, Gustavo Canavire-Bacarreza, and Luis Castro Peñarrieta
Publication Date:
10-2017
Content Type:
Working Paper
Institution:
Institute for Advanced Development Studies (INESAD)
Abstract:
Average treatment effects estimands can present significant bias under the presence of outliers. Moreover, outliers can be particularly hard to detect, creating bias and inconsistency in the semi-parametric ATE estimads. In this paper, we use Monte Carlo simulations to demonstrate that semi-parametric methods, such as matching, are biased in the presence of outliers. Bad and good leverage points outliers are considered. The bias arises because bad leverage points completely change the distribution of the metrics used to define counterfactuals. Whereas good leverage points increase the chance of breaking the common support condition and distort the balance of the covariates and which may push practitioners to misspecify the propensity score. We provide some clues to diagnose the presence of outliers and propose a reweighting estimator that is robust against outliers based on the Stahel-Donoho multivariate estimator of scale and location. An application of this estimator to LaLonde’s (1986) data allows us to explain the Dehejia and Wahba (2002) and Smith and Todd (2005) debate on the inability of matching estimators to deal with the evaluation problem.
Topic:
Economics, Econometrics, Methods, and Counterfactuals
Political Geography:
Global