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• Statistical Inference 统计推断
• Statistical Computing 统计计算
• Advanced Probability Theory 高等概率论
• Advanced Mathematical Statistics 高等数理统计学
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 经济代写|产业经济学代写Industrial Economics代考|Summary of firm-level findings

In the declining products sample, small producers suffered disproportionately high mortality rates, whereas large-share firms made more frequent incremental reductions of capacity. Nearly all plant closures by ‘bottom third’ producers were exits, whereas ‘top third’ firms typically remained as producers despite closure of some plants. When exit and incremental divestment are combined, the total capacity reductions made by large and small firms were about equal. For survivor firms in the most steeply declining products there is evidence that firm sizes converged owing to more rapid divestment by the largest producers.
These findings at the firm level can be viewed as consistent with both the ‘shakeout’ model and $\mathrm{G} \& \mathrm{~N}$ (1990). Many of the findings are also consistent with a more naive model of divestment. Assume that (1) large firms differ from small firms solely in the number of plants that they operate and (2) the probability of plant closure is uncorrelated with firm size. Under these conditions one would naturally observe more frequent exits by small producers, even though the rate of divestment, on average, is independent of firm size. The one finding inconsistent with this naive model is that of convergence within the cohort of surviving firms. A further basis for rejecting the naive model is provided by findings on plant-level divestment, reported in the next section.

## 经济代写|产业经济学代写Industrial Economics代考|Analysis of plant closures

Here I consider divestment at the plant level, using logit analysis to identify factors that influenced firms’ decisions to close individual plants. The results show that small plants were more likely to be closed; but controlling for plant size, the probability of closure increased with the firm’s capacity share, as predicted by the G\&N (1990) model. Additional factors that might serve as ‘exit barriers’ along the lines proposed by Caves and Porter (1976) and Harrigan (1980) are also evaluated.

The lower half of table $5.7$ gives summary statistics on multi-plant operation and average plant scale by size class of producer in the peak year. Larger producers typically operated multiple plants. Firms in the ‘top third’ category operated an average of $2.8$ plants in the peak year, as compared with $1.3$ plants for ‘bottom third’ producers. For 12 of the 17 products included in table 5.7, the largest producer was a multi-plant firm.

Plant scale was measured relative to the capacity of the largest plant in the industry. For producers in the ‘top third’ category, an average plant had capacity equal to 70 per cent of the largest industry plant for that product. Plants operated by firms in the ‘middle third’ category were of nearly this size. However, firms in the ‘bottom third’ operated plants that were, on average, less than half as large. Hence, significant scalerelated cost penalties were experienced by many ‘bottom third’ producers.

# 产业经济学代考

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