Subsampling the distribution of diverging statistics with applications to finance

In this paper we propose a subsampling estimator for the distribution of statistics diverging at either known or unknown rates when the underlying time series is strictly stationary and strong mixing. Based on our results we provide a detailed discussion of how to estimate extreme order statistics with dependent data and present two applications to assessing financial market risk. Our method performs well in estimating Value at Risk and provides a superior alternative to Hill's estimator in operationalizing Safety First portfolio selection.     

International trade and unionization: Evidence from India

We exploit exogenous variation in tariffs to examine the impact of import competition on unionization and union wages in a developing country. Using a combination of nationally representative household data (National Sample Survey Organization) and nationally representative industry‐level data (Annual Survey of Industries) from India, we find that net‐import industries that experienced larger cuts in tariffs also experienced larger declines in unionization. In addition, we find that these industries also experienced larger increases in union wages. These results are consistent with the predictions of an efficient bargaining framework that we extend to endogenize the union formation decision by allowing for a fixed cost of union formation. We also conduct a back‐of‐the‐envelope calculation to show that the total wage gains to unionized workers marginally exceed the total wage losses to deunionized workers.     

A new perspective on the exporter productivity premium: online trade

We use a unique firm-level data set including 9000 companies from 26 European Union countries covering four different sectors to take a close look at the relationship between online exports and productivity. The online exporter productivity premium is estimated using different techniques (ordinary least squares, quantile regressions and robust estimation). Results consistently indicate that the estimated online exporter productivity premium is statistically different from zero, positive and significant from an economic point of view. European online exporters, according to these results, are approximately 2% more productive than non-online exporters. Productivity differences between firms could be related to variables that are not included in the empirical model. More research would be needed to address this issue in the future.     

Measuring new product success: an empirical investigation of Australian SMEs

New product development (NPD) has long been recognised as one of the corporate core functions. However, measuring new product success has remained elusive. This paper attempts to examine several conceptual issues underlining the measurement of new product success and the measurement practice adopted in Australian small and medium enterprises (SMEs). The sample included 276 SMEs from two most innovative industries: chemical and machinery industries. Results have indicated that four factors underline the commonly used success measurement: financial performance, objective market acceptance, subjective market acceptance, and product-level measures. These four factors are related to each other and can be used to well predict the overall measurement. The most frequently used specific measures in Australian SMEs are customer acceptance, customer satisfaction, product performance, and quality.     

An automatic Portmanteau test for serial correlation

This article introduces a data-driven Box–Pierce test for serial correlation. The proposed test is very attractive compared to the existing ones. In particular, implementation of this test is extremely simple for two reasons: first, the researcher does not need to specify the order of the autocorrelation tested, since the test automatically chooses this number; second, its asymptotic null distribution is chi-square with one degree of freedom, so there is no need of using a bootstrap procedure to estimate the critical values. In addition, the test is robust to the presence of conditional heteroskedasticity of unknown form. Finally, the proposed test presents higher power in simulations than the existing ones for models commonly employed in empirical finance.