Job growth in early transition: Comparing two paths*

Small start‐up firms are the engine of job creation in early transition. We ask about differences in their growth across two different transition economies: Estonia, which experienced rapid destruction of pre‐existing firms, and the Czech Republic, which reduced the old sector gradually. We find that the majority of job growth corresponds to within‐industry reallocation. The within‐industry growth of small start‐up firms is similar in the two countries, in line with the convergence to Western industry firm‐size distributions. We also find similar patterns in the evolution of wage differentials between start‐ups and old firms and small differences in the extent of low‐wage employment in start‐ups across the two transition paths. JEL Classifications: J2, J3, J4, L1, O1, P2.     

Rural taxation and government regulation in China

This paper places the problem of Chinese rural taxation in the context of government regulation and seeks to present an integrated theoretical framework of Chinese rural development in the past two decades. Our theoretical framework reconciles the seemingly contradictory facts that the average level of rural taxation relative to rural net income did not increase quickly from 1990, but rural taxation became a very serious problem in this period. Our findings suggest that this is in large part due to increases in rural income disparity from 1990 and uneven tax distribution among different income groups. We argue that differentiated enforcement of government regulations such as grain procurement and birth control play an important role in the rural taxation problem, and more generally, the problem of local government expansion and rising rural income disparity. The empirical findings support our hypotheses.     

Why are Small Firms Different? Managers’ Views

Do incentives differ between large and small organizations? Results from a representative survey of compensation managers are used to shed light on the issues. I find that (i) small establishments rely less on pecuniary incentives, and have a significantly more hostile attitude towards incentive schemes based on competition and relative rewards; (ii) large units are more vulnerable to mechanisms of efficiency wages, effects that remain even after controlling for differences in monitoring ability; (iii) large units are more prone to indicate that negative reciprocity is important, and that their employees care about relative pay. I argue that these findings fit with behavioral stories of incentives and motivation, in particular those stressing group interaction effects, inequity aversion and gift exchange.     

BUILDING CARS TO CUSTOMER ORDER — WHAT DOES IT MEAN FOR INBOUND LOGISTICS OPERATIONS?

The automotive industry is undergoing a strategic transition. Cost pressure from rising stock levels in the market and increasing incentives needed to sell these vehicles are forcing vehicle manufacturers to rethink their prevalent “stock‐push” approach, building vehicles against a forecast and selling from stock, in favor of a stock‐less “build‐to‐order” order fulfillment strategy. More responsive order fulfillment at the vehicle manufacturer level however will not only require flexible and responsive component supply, but will also have wide ramifications for the logistics operations. Based on three case studies of major inbound logistics operations, this exploratory study assesses their ability to support such a build‐to‐order approach, as well as the potential implications of such transition. The paper concludes with a set of general strategies for how these implications could be mitigated.     

Estimating the Size of a Criminal Population from Police Records Using the Truncated Poisson Regression Model

The truncated Poisson regression model is used to arrive at point and interval estimates of the size of two offender populations, i.e. drunk drivers and persons who illegally possess firearms. The dependent capture–recapture variables are constructed from Dutch police records and are counts of individual arrests for both violations. The population size estimates are derived assuming that each count is a realization of a Poisson distribution, and that the Poisson parameters are related to covariates through the truncated Poisson regression model. These assumptions are discussed in detail, and the tenability of the second assumption is assessed by evaluating the marginal residuals and performing tests on overdispersion. For the firearms example, the second assumption seems to hold well, but for the drunk drivers example there is some overdispersion. It is concluded that the method is useful, provided it is used with care.     

PLANNING MULTIPLE LOCATION INVENTORIES

Supplying customer demand from comparable alternate inventory locations when an item is out of stock at its primary stocking point creates a virtual inventory for that item. The expectation is that if more inventories can be drawn upon, the inventory for an item would be lower, the fill rate would be higher, or both. While generally true that safety stocks will be lower, regular stocks, on the other hand, may rise with such cross filling of demand. In this study, a methodology is developed that balances the cross filling effects on both regular and safety stocks for determining whether an inventoried item should be cross‐filled. An example and guidelines are given to show how the methodology can be simplified and applied in practice.     

融资优序与行业管制——兼析中国上市公司“异常融资优序”现象

企业融资先通过内部资金进行,然后再通过银行借款或发行低风险的债券,最后才采用股票,这种融资的“先后顺序”是企业出于降低融资成本和防止剩余利润被分享所做出的理性选择,这就是融资优序理论。本文认为,寡头竞争所形成的行业进入壁垒为优序融资的实现提供了必须的市场环境,其资金使用方式能够优化资源配置,提高资金的使用效率。融资优序理论在发达市场经济国家得到了实践的验证,但在我国上市公司中却存在“异常融资优序”(Abnormal pccking Order)现象,即外部资金优于内部资金,外部资金中股权融资优于债权融资。其原因在于,中国市场经济不太完善,缺乏通过寡头竞争自发形成的行业进入壁垒。本文认为只有采取行业管制手段,设置一定的行业进入壁垒,才能实现优序融资,从而达到优化资源配置的目的。     

Dominance Statistics: A Simulation Study on the d Statistic

Quality &; Quantity - Cliff (1993) has proposed the use of a measure of effect size alternative to traditionalmean differences: δ {? = Pr(xi1 &;gt; xj2) - Pr(xi1 &;lt; xj2)}which,...     

Sample Design and Allocation for Random Digit Dialling

Sample design and sample allocation methods are developed for random digit dialling in household telephone surveys. The proposed method is based on a two-way stratification of telephone numbers. A weighted probability proportional to size sample allocation technique is used, with auxiliary variables about the telephone coverage rates, within local telephone exchanges of each substrata. This makes the sampling design nearly “self-weighting” in residential numbers when the prior information is well assigned. A computer program generates random numbers for the local areas within the existing phone capacities. A simulation study has shown greater sample allocation gain by the weighted probabilities proportional to size measures over other sample allocation methods. The amount of dialling required to obtain the sample is less than for proportional allocation. A decrease is also observed on the gain in sample allocation for some methods through the increasing sample sizes.     

Robustness issues in multilevel regression analysis

A multilevel problem concerns a population with a hierarchical structure. A sample from such a population can be described as a multistage sample. First, a sample of higher level units is drawn (e.g. schools or organizations), and next a sample of the sub‐units from the available units (e.g. pupils in schools or employees in organizations). In such samples, the individual observations are in general not completely independent. Multilevel analysis software accounts for this dependence and in recent years these programs have been widely accepted. Two problems that occur in the practice of multilevel modeling will be discussed. The first problem is the choice of the sample sizes at the different levels. What are sufficient sample sizes for accurate estimation? The second problem is the normality assumption of the level‐2 error distribution. When one wants to conduct tests of significance, the errors need to be normally distributed. What happens when this is not the case? In this paper, simulation studies are used to answer both questions. With respect to the first question, the results show that a small sample size at level two (meaning a sample of 50 or less) leads to biased estimates of the second‐level standard errors. The answer to the second question is that only the standard errors for the random effects at the second level are highly inaccurate if the distributional assumptions concerning the level‐2 errors are not fulfilled. Robust standard errors turn out to be more reliable than the asymptotic standard errors based on maximum likelihood.