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英文文献：GDP and convergence in modern times-GDP与现代趋同
英文文献作者：Emanuele Felice
英文文献摘要：
In this chapter I discuss historical estimates of GDP at both the national and the regional level, and their application for assessing economic performance in modern times. Having been invented in (and conceived for) industrial capitalist societies, GDP has stronger informative power in those contexts where industry and services, and market exchange, retain the lion’s share of production. In modern times, when comparing the series available for different countries, there are three major methodological problems to be acknowledged and possibly addressed: the dissimilarity of the quantity series and related proxies; deflation through purchasing power parities distant in time; and the differences in the base year used to construct GDP constant price (Laspeyres) indices (the latter issue may be less widely recognized, but it may have a remarkable impact). The way the estimates are constructed also has a bearing upon the statistical tools and models we should use to interpret them; owing to the lack of reliable long-run series, cross-sectional techniques are often preferable to time series analysis; provided we have reliable estimates, growth accounting - decomposing GDP growth into productivity and industry mix effects - may provide important clues about the choice between theoretical approaches; not least for the quality of our data, cross-country convergence models based on conditioning variables should always be supplemented by historical information from qualitative sources and case studies. More generally, cliometricians should prove themselves capable of adapting their models to different historical contexts and relativizing findings to the limits of their estimates.
在本章中，我将讨论历史上对国家和地区GDP的估计，以及它们在现代经济绩效评估中的应用。GDP诞生于工业资本主义社会(并为其构想)，在工业、服务和市场交换占据了生产的大部分份额的情况下，它具有更强的信息威力。在现代，在比较不同国家可用的数列时，需要承认并可能解决三个主要的方法问题:数量数列和有关代理的不同;遥远的购买力平价导致的通货紧缩;以及用于构建GDP不变价格指数(Laspeyres)的基准年的差异(Laspeyres指数可能没有那么广泛的认识，但它可能会产生显著的影响)。估算的构建方式也会影响我们用来解释它们的统计工具和模型;由于缺乏可靠的长期序列，横断面技术往往比时间序列分析更可取;如果我们有可靠的估计，增长核算——将GDP增长分解为生产率和行业混合效应——可能为选择理论方法提供重要线索;尤其是对于我们的数据质量，基于条件变量的跨国收敛模型应该总是由定性来源和案例研究的历史信息来补充。更普遍地说，气象学家应该证明自己有能力调整他们的模型以适应不同的历史背景，并将研究结果相对化以适应他们估计的极限。
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