Finite sample properties of estimators for autoregressive moving average models

We analyze by simulation the properties of three estimators frequently used in the analysis of autoregressive moving average time series models for both nonseasonal and seasonal data. The estimators considered are exact maximum likelihood, exact least squares and conditional least squares. For samples of the size commonly found in economic applications, the estimators are compared in terms of bias, mean squared error, and predictive ability. The reliability of the usually calculated confidence intervals is assessed for the maximum likelihood estimator.     

Television-Induced Tourism: Evidence from Croatia

Atlantic Economic Journal - This paper analyzes the extent to which the filming of the popular television show Game of Thrones affected tourism in the Croatian city of Dubrovnik. Using monthly data...     

Free-Agency and the Competitiveness of Major League Baseball

I investigate whether the removal of the reserve clause in professional baseball affected the competitive nature of the industry in the context of whether the distribution of team wins has been affected by free-agency. Unlike previous studies which use the standard deviation of winning percentage, I use a more sensitive measure of parity. I calculate the deviations of the Herfindahl-Hirschman Index of team wins from the competitive ideal during 1920 to 1996 and relate them to player-talent distribution and structural changes in the industry. I isolate the structural effect of free-agency and find that it has adversely affected the parity of the American League but that it has had no statistical influence on the parity of the National League.     

The great Canadian recovery: The impact of COVID-19 on Canada's labour market

The Canadian labour market experienced a period of unprecedented turmoil following the onset of the COVID-19 pandemic. We analyze the main changes using standard labour force statistics and new data on job postings. Envisaging a phase of temporary severing of employment relationships followed by a phase of more standard labour market search and matching, we use stock and flow data to understand key developments. We find dramatic changes in employment, unemployment and labour market attachment in the first few months of the pandemic and a broad though gradual recovery through to the end of 2021.     

The determinants of market-wide issue cycles for initial public offerings

This paper identifies the determinants of market-wide issue cycles for initial public offerings (IPOs) using an autoregressive conditional count model. We consider whether IPO volume is related to business conditions, investor sentiment, and time variation in adverse selection costs caused by asymmetric information between managers and investors. We provide evidence indicating that time variation in business conditions and investor sentiment are important determinants of monthly issue activity. By contrast, time variation in adverse selection costs does not significantly affect IPO volume.