Michael Halperin

Technical Performance and Firm Size: Analysis of Patents and Publications of U.S. Firms

This study focuses on the scientific output of firms of different sizes in different industries in the U.S. Both patents, and papers and publications are used as measures of technical output. Data from two samples of firms, one consisting of 225 large firms (annual sales at least

A Two-Staged Benchmarked Decision Support System Using DEA Profiles of Efficiency

250 million and minimum annual R&D budget of

Outlier Screening Protocols for Stock Market Studies: A Suggested Screen

1 million) and the other consisting of 248 small and medium sized firms (annual sales between

Comparing the Rankings of MBA Curricula: Do Methodologies Matter?

10 to

Prevalence profiling: a judgmental context for evaluating initial sample size projections in the audit context

200 million and annual R&D budget at least

Events and EVENTUS: Understanding and Facilitating Event Studies

10 thousand) have been presented here. The study shows that determinants of R&D expenditure are different in firms of different sizes. For the large firms, R&D expenditure depends on net income as well as its size, measured in terms of annual sales. For small size firms, R&D expenditure is closely related with sales, rather than the net income. For large firms, R&D expenditure is related to both sales and income, the latter being more important than the former. The two output measures, patents and papers are correlated, but the correlation is not a very strong one for small firms. Patent and papers are correlated significantly with both R&D expenditure as well as annual sales. The firms growth is not linked with patents. On the contrary, there is a negative relationship between patent and R&D growth and patent and income growth in the case of small firms. Papers are not linked with growth variables for small firms. Finally, this study confirms the hypothesis that small firms are more productive in innovation than the large firms. Small firms are more efficient than their larger competitors in terms of patents and papers per million dollars of R&D expenditure.

CFO resignations: their underlying performance and behavioural context

Abstract Using the BvD BankScopeTM database through Wharton Research Data ServicesTM, we identified for 2002 through 2005 all of the US national banks listed on the NY or NASDAQ stock exchanges. This yielded for each year about 120 banks. For each year, we categorized these banks into three size groups based upon total assets. We then: (1) developed for each year using the standard CCR DEA analysis those banks that were CCR efficient, (2) using variables suggested in the literature as being important in characterizing the relative performance of banks, we developed profiles of the differences between the efficient and relatively non-efficient banks for each of the three size categories by year. This was the first stage in the DEA profiling. For the second stage, again for each year by size grouping, we: (1) calculated the Super-Efficiency [SE] scores as proposed by Andersen and Petersen (1993) for the set of CCR efficient banks, (2) developed High and Low SE groups using a median-split of these Super-Efficiency scores, and (3) profiled these SE-High and SE-Low groups. Results: we: (1) developed and illustrated a simple DEA DSS heuristic that could be used by decision makers to identify the driver variables that may be acted upon to manage their risk by moving their banks into their target efficiency group, (2) demonstrated that size is an important category variable in understanding the profiled performance of banks, (3) determined that the Super-Efficiency profiles are refinements of the CCR categorization, and (4) found that there are size-related stationarity differences among the banks which have risk implications for the various size groupings.

An investigation of the relationship between Corporate Governance and firm performance: the market emergence of the Autocratic firm

In the Data Streaming world, screening for outliers is an often overlooked aspect of the data preparation phase, which is needed to rationalize inferences drawn from the analysis of data. In this paper, we examine the effects of three outlier screens: A Trimming Window, The Box-Plot Screen and the Mahalanobis Screen on the market performance profile of firms traded on the NASDAQ and NYSE. From among seven screening combinations tested, we identify a single screening protocol that is the sequential application of all three screens. This protocol is: (1) simple to program, (2) significantly effective statistically and (3) does not compromise power. This important result demonstrates that for the usual data used by Financial Analysts there is one screening protocol that can be relied upon to satisfy the outlier assumption of the regression model used in generating the usual firm CAPM Return and Risk profile. JEL: Classification: G11, G12, G32, and G30

Annual Reports: Preserving and Disseminating a Source for Business History

We created a matrix of rankings of MBA curricula by six publishers and used a standard SAS program to supply missing data. We then examined the resulting construct to assess the publishers’ ranking similarity and their change over a four year period.

Client risk calibration in PCAOB audits: an analytical procedures panel risk assignment protocol

The basis of the certification audit, in a non-forensic context is a random sample of sufficient size to create the evidence needed to justify the audit opinion. A key variable in executing this Public Company Accounting Oversight Board (PCAOB) best practices sampling requirement is the prevalence of accounts in error and the related error of and in those accounts. In this paper, we present an integrated sampling approach using the COSO-event (the number of accounts in error) and the substantive valued-event (the error in the accounts) perspectives. We focus on creating pre-sample launch decision-making information by examining the false positive and the false negative error indications over various prevalence error-ranges. We have also developed a decision support system (DSS) that we have introduced as part of our academic consulting to a PCAOB certified public accounting LLP and also have used extensively in the delivery of our auditing and assurance course. This DSS is available free as a download and there are no restrictions on its use.