1972 enterprise statistics.

Chiefly tables.

1977 enterprise statistics

"ES77-2."

Parametric VaR with goodness-of-fit tests based on EDF statistics for extreme returns

Parametric VaR (Value-at-Risk) is widely used due to its simplicity and easy calculation. However, the normality assumption, often used in the estimation of the parametric VaR, does not provide satisfactory estimates for risk exposure. Therefore, this study suggests a method for computing the parametric VaR based on goodness-of-fit tests using the empirical distribution function (EDF) for extreme returns, and compares the feasibility of this method for the banking sector in an emerging market and in a developed one. The paper also discusses possible theoretical contributions in related fields like enterprise risk management (ERM). © 2013 Elsevier Ltd.

A Distributive Comparison of Enterprise Size in Korea and Taiwan

Research to date on the economic development of the Republic of Korea and Taiwan has frequently contrasted the two economies by depicting the former as centered on large-scale enterprises and the latter on small and medium-size enterprises (SMEs). The purpose of this study is to see if the appropriateness of this perception will also be verified by the statistical data. In Section I the authors utilized census data on the Korean and Taiwanese manufacturing sectors to compare the distribution pattern of the sizes of enterprises in the two economies. However, on examining the available data for making this comparison, the authors discovered that for Korea the statistics provided are those at the level of the establishment (a physical unit engaging in industrial activities such as a factory, workshop, office, or mine) while the statistics for Taiwan are those at the enterprise level. Mindful of this difference, the authors looked at the portion of the economy accounted for by large-scale establishments in Korea that employed 500 workers or more and by enterprises in Taiwan employing the same number of workers, and they discovered that the portion that these large-scale businesses account for, especially in the area of output, has steadily declined since the 1980s. When comparing the share of total production that these large-scale establishments/enterprises account for in the two economies, the authors concluded that those in Korea accounted for a larger share of that economy's production than did their counterparts in Taiwan. The authors then compared the portion of the economy accounted for by establishments in Korea and enterprises in Taiwan that employed less than ten workers, and they found that the portion of the two economies that these very small-scale production units accounted for has also been on the decline. Section II compares the portions of the two economies accounted for by large business groups. After comparing the percentage of GDP accounted for by the total sales of these business groups, the authors found that large business groups in Korea have played a far more important role in Korean economy than has been the case for such groups in Taiwan. This difference in the importance of such business groups in the two economies has also played an significant part in fostering the perceived dichotomy of large-scale enterprises playing the important role in Korea versus SMEs being the important players in Taiwan. Section III compares the percentage of total exports accounted for by SMEs, and shows that SMEs in Taiwan account for a larger share of exports than do their counterparts in Korea. This section also shows that in Taiwan the share of export sales for SMEs has consistently exceeded that for non-SMEs, while in Korea the relationship between enterprise size and the rate of export sales has been directly proportional. This difference in the size of the major export players is another factor fostering the perception of the Korean economy being centered on big business while Taiwan's is on SMEs. Although there were difficulties and limitations when comparing the data of the two economies, the statistical comparison undertaken in this study shows that in general big business has played the major role in the development of the Korean economy while in Taiwan's economic development this role has been played by SMEs. Thus the statistical data also verifies the perceived dichotomy of these two economies.

History of Saginaw county from the year 1819 down to the present time. Comp. from authentic records and other sources: traditionary accounts, legends, anecdotes, &c., with valuable statistics, and notes of its resources, and general information concerning its advantages: also a business directory of each of the three principal towns in the county.

Mode of access: Internet.

An empirical evaluation of imputation accuracy for association statistics reveals increased type-I error rates in genome-wide associations

Background: Genome wide association studies (GWAS) are becoming the approach of choice to identify genetic determinants of complex phenotypes and common diseases. The astonishing amount of generated data and the use of distinct genotyping platforms with variable genomic coverage are still analytical challenges. Imputation algorithms combine directly genotyped markers information with haplotypic structure for the population of interest for the inference of a badly genotyped or missing marker and are considered a near zero cost approach to allow the comparison and combination of data generated in different studies. Several reports stated that imputed markers have an overall acceptable accuracy but no published report has performed a pair wise comparison of imputed and empiric association statistics of a complete set of GWAS markers. Results: In this report we identified a total of 73 imputed markers that yielded a nominally statistically significant association at P < 10(-5) for type 2 Diabetes Mellitus and compared them with results obtained based on empirical allelic frequencies. Interestingly, despite their overall high correlation, association statistics based on imputed frequencies were discordant in 35 of the 73 (47%) associated markers, considerably inflating the type I error rate of imputed markers. We comprehensively tested several quality thresholds, the haplotypic structure underlying imputed markers and the use of flanking markers as predictors of inaccurate association statistics derived from imputed markers. Conclusions: Our results suggest that association statistics from imputed markers showing specific MAF (Minor Allele Frequencies) range, located in weak linkage disequilibrium blocks or strongly deviating from local patterns of association are prone to have inflated false positive association signals. The present study highlights the potential of imputation procedures and proposes simple procedures for selecting the best imputed markers for follow-up genotyping studies.

Statistics of opinion domains of the majority-vote model on a square lattice

The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.

Protein fold recognition without Boltzmann statistics or explicit physical basis

We present a fast method for finding optimal parameters for a low-resolution (threading) force field intended to distinguish correct from incorrect folds for a given protein sequence. In contrast to other methods, the parameterization uses information from >10(7) misfolded structures as well as a set of native sequence-structure pairs. In addition to testing the resulting force field's performance on the protein sequence threading problem, results are shown that characterize the number of parameters necessary for effective structure recognition.

Critical values for unit root and cointegration test statistics - the use of response surface equations

This note considers the value of surface response equations which can be used to calculate critical values for a range of unit root and cointegration tests popular in applied economic research.

Information internalization and hurdle rates in small and medium enterprise internationalization

We investigate the role of information in the internationalization of small and medium enterprises (SMEs). Information internalization is fundamentally antecedent to SME internationalization and is being facilitated increasingly by recent important trends. We offer a conceptual explanation and related propositions on information internalization, emphasizing hurdle rate theory for ascertaining the acceptability of firms' internationalization projects.

Accelerating seismic energy release and evolution of event time and size statistics: Results from two heterogeneous cellular automaton models

The evolution of event time and size statistics in two heterogeneous cellular automaton models of earthquake behavior are studied and compared to the evolution of these quantities during observed periods of accelerating seismic energy release Drier to large earthquakes. The two automata have different nearest neighbor laws, one of which produces self-organized critical (SOC) behavior (PSD model) and the other which produces quasi-periodic large events (crack model). In the PSD model periods of accelerating energy release before large events are rare. In the crack model, many large events are preceded by periods of accelerating energy release. When compared to randomized event catalogs, accelerating energy release before large events occurs more often than random in the crack model but less often than random in the PSD model; it is easier to tell the crack and PSD model results apart from each other than to tell either model apart from a random catalog. The evolution of event sizes during the accelerating energy release sequences in all models is compared to that of observed sequences. The accelerating energy release sequences in the crack model consist of an increase in the rate of events of all sizes, consistent with observations from a small number of natural cases, however inconsistent with a larger number of cases in which there is an increase in the rate of only moderate-sized events. On average, no increase in the rate of events of any size is seen before large events in the PSD model.