Cointegration and control: Assessing the impact of events using time series data

Control groups can provide counterfactual evidence for assessing the impact of an event or policy change on a target variable. We argue that fitting a multivariate time series model offers potential gains over a direct comparison between the target and a weighted average of controls. More importantly, it highlights the assumptions underlying methods such as difference in differences and synthetic control, suggesting ways to test these assumptions. Gains from simple and transparent time series models are analysed using examples from the literature, including the California smoking law of 1989 and German reunification. We argue that selecting controls using a time series strategy is preferable to existing data‐driven regression methods.     

An empirical note about estimation and forecasting Latin American Forex returns volatility: the role of long memory and random level shifts components

Portuguese Economic Journal - A set of RLS-type models with ARMA and ARFIMA dynamics is estimated and compared in a forecasting exercise with ARFIMA, GARCH and FIGARCH models. It is an extension of...     

Hayek on the essential dispersion of market knowledge

The Review of Austrian Economics - A key insight in Hayek’s thought is the importance of so-called “local knowledge” in economic activity. In The Fatal Conceit, he states that...     

Capital gains lock-in and governance choices

Differences in accrued gains and investors’ tax-sensitivity induce variation in a capital gains lock-in effect across mutual funds even for the same stock at the same time. Exploiting this variation, we show this effect influences funds’ governance decisions: higher capital gains decrease the likelihood a fund exits prior to contentious votes and increase the likelihood a fund votes against management. Consistent with tax motivation, these findings are concentrated among funds with tax-sensitive investors. Further, high aggregate capital gains across funds holding a stock predict a higher likelihood management loses a vote and a lower likelihood a contentious vote is proposed.     

The US financial crisis and corporate dividend reactions: for better or for worse?

Review of Quantitative Finance and Accounting - We examine how changes in dividend policy in 2008 as the financial crisis was unfolding influenced firm risk-adjusted returns in the following years....     

Information flows and crashes in dynamic social networks

We develop a dynamic model of information transmission and aggregation in social networks in which continued membership in the network is contingent on the accuracy of opinions. Agents have opinions about a state of the world and form links to others in a directed fashion probabilistically. Agents update their opinions by averaging those of their connections, weighted by how long their connections have been in the system. Agents survive or die based on how far their opinions are from the true state. In contrast to the results in the extant literature on DeGroot learning, we show through simulations that for some parameterizations the model cycles stochastically between periods of high connectivity, in which agents arrive at a consensus opinion close to the state, and periods of low connectivity, in which agents’ opinions are widely dispersed.

     

Missing the Popular Vote: Pitfalls in US Democracy and Reform Proposals

Intereconomics - Only a few years ago, it was a widespread belief that globalisation would trigger processes of democratisation worldwide. However, even old and established democracies such as the...     

The Cost of War: A Comment and a Reply

Intereconomics - In the July/August issue of Intereconomics, Ilona Sologoub argued that increasing the cost of war would limit the ability of an authoritarian state to wage a war. Here, Charles D....     

The Impact of Automated Reminders on Credit Outcomes: Results from an Experimental Pilot Program

This study evaluates the impact of an automated reminder program designed to help credit counseling consumers manage their payment obligations and financial goals. Credit counseling consumers were randomly assigned to receive reminders linked to their financial goals and payment obligations for one year after an initial credit counseling session. We find that consumers offered reminders were 21% less likely than the control to experience severe (60+ day) payment delinquencies and were 12% less likely to experience a 30+ day delinquency. At the same time, these consumers saw a 10.5 point increase in credit scores relative to the control group. There were no significant impacts on total credit card balances or installment debt levels. This analysis provides promising evidence that automated reminders can provide an important complement to traditional credit counseling when it comes to improving consumers' credit profiles and does so at a fairly low cost.