Marcel Voia

The Impact of Initial Financial State on Firm Duration Across Entry Cohorts

Recent theories of industry dynamics emphasize the role of financial frictions in determining post entry performance of firms. Testing these theories has been difficult because of the lack of financial data on small, young and private firms. Using a unique data set, T2LEAP, this paper considers the survival of new firms in Canadian manufacturing from a financial perspective. Duration analysis quantifies the effects of firm, industry and aggregate factors. Findings show that nonlinear effects are found with firm leverage. Finally, likelihood decompositions offer insights into the contributing factors to firm hazard for nine entry cohorts during the period 1985–1997.

The Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification

We consider an empirical estimation of the Environmental Kuznets Curve (EKC) for carbon dioxide and sulphur, with a focus on confidence set estimation of the tipping point. Various econometric – parametric and nonparametric – methods are considered, reflecting the implications of persistence, endogeneity, the necessity of breaking down our panel regionally, and the small number of countries within each panel. In particular, we propose an inference method that corrects for potential weak-identification of the tipping point. Weak identification may occur if the true EKC is linear while a quadratic income term is nevertheless imposed into the estimated equation. Relevant literature to date confirms that non-linearity of the EKC is indeed not granted, which provides the motivation for our work. Viewed collectively, our results confirm an inverted U-shaped EKC in the OECD countries but generally not elsewhere, although a local-pollutant analysis suggest favorable exceptions beyond the OECD. Our measures of uncertainty confirm that it is difficult to identify economically plausible tipping points. Policy-relevant estimates of the tipping point can nevertheless be recovered from a local-pollutant long-run or non-parametric perspective.

Functional Principal Component Analysis of Density Families with Categorical and Continuous Data on Canadian Entrant Manufacturing Firms

This article investigates the evolution of firm distributions for entrant manufacturing firms in Canada using functional principal components analysis. This methodology describes the dynamics of firms by examining production variables, size, and labor productivity, and a financial variable, leverage (debt-to-asset ratio). We adapt the canonical functional principal components analysis to allow for the inclusion of qualitative information in the form of discrete variables, industry, and region, to capture market structure differences, which is shown to change the dynamics of firm size and labor productivity distributions only. We also perform various tests with the null hypothesis that the distributions are equal across time. When accounting for industry and regional categories, there is a substantial fall in the number of rejections of the null hypothesis of equality for size and labor productivity, which is not the case for leverage. These results show the importance of including qualitative information to account for potential heterogeneity when applying functional principal component analysis to firm-level data. Finally, the methodology finds a correlation between the evolution of variable distributions and macroeconomic factors. This article has supplementary material online.

Nonlinear Difference-in-Difference Treatment Effect Estimation: A Distributional Analysis

This chapter uses the nonlinear difference-in-difference (NL-DID) methodology developed by Athey and Imbens (2006) to estimate the effects of a treatment program on the entire distribution of an outcome variable. The NL-DID estimates the entire counterfactual distribution of an outcome variable that would have occurred in the absence of treatment. This chapter extends the Monte Carlo results in Athey and Imbenss (2006) to assess the efficacy of the NL-DID estimators in finite samples. Furthermore, the NL-DID methodology recovers the entire outcome distribution in the absence of treatment. Further, we consider the empirical size and power of tests statistics for equality of mean, medians, and complete distributions as suggested by Abadie (2002). The results show that the NL-DID estimator can effectively be used to recover the average treatment effect, as well as the entire distribution of the treatment effects when there is no selection during the treatment period in finite samples.

What are the significant determinants of entrepreneurship

In this paper, we use data from the OECD structural and demographic business statistics database and the entrepreneurship indicators programme to test the impact of a broad set of cultural, institutional, and economic determinants on the birth of new enterprises, the death rate of enterprises, and a net and gross measure of the two. We find that while all determinant categories exhibit some degree of explanatory power, the categories of access to knowledge, entrepreneurial capabilities and access to finance rank highest as determinants of entrepreneurial activity.

A Retrospective Analysis of Employment Duration: Evidence from the Second Half of the Twentieth Century

Popular perception holds that average employment durations have declined in recent decades. However, most studies conclude that the proportion of long-term employment relationships has remained remarkably stable over time. To shed light on this discrepancy we use distribution analysis to systematically track changes in Canadian employment durations over the second half of the 20th century. The analysis reveals that earlier cohorts were more likely to have longer employment durations than later cohorts and that there are shifts in proportions between longer and shorter work episodes with employment durations declining sharply for men and mixed results for women.

Tail Risk in a Retail Payments System

Abstract In this paper, we study a credit risk (collateral) management scheme for the Canadian retail payment system designed to cover the exposure of a defaulting member. We estimate ex ante the size of a collateral pool large enough to cover exposure for a historical worst-case default scenario. The parameters of the distribution of the maxima are estimated using two main statistical approaches based on extreme value models: Block-Maxima for different window lengths (daily, weekly and monthly) and Peak-over-Threshold. Our statistical model implies that the largest daily net debit position across participants exceeds roughly

Duration of new firms: The role of startup financial conditions, industry and aggregate factors

1.5 billion once a year. Despite relying on extreme-value theory, the out of sample forecasts may still underestimate an actual exposure given the absence of observed data on defaults and financial stress in Canada. Our results are informative for optimal collateral management and system design of pre-funded retail-payment schemes.