Demand Systems Estimation With Microdata: A Censored Regression Approach
针对家庭支出调查中大量商品零消费导致的删失问题，提出一种计算简单、一致且渐近有效的删失回归方法，并与未删失技术的结果进行比较，对从事需求系统估计的计量经济学研究者有参考价值。
Demand systems estimation increasingly makes use of household-level microdata, mainly to measure the effects of demographic variables. Data based on these household-expenditure surveys present a major estimation problem. For any given household, many of the goods have zero consumption, implying a censored dependent variable. Techniques which do not take this censored dependent variable into account will yield biased results. We utilize a censored regression approach that is computationally simple, consistent, and asymptotically efficient. The results are then presented and compared with those obtained using an uncensored technique.