PurposeThis study aims to apply a proposed methodology for calculating spatial prices in a heterogeneous country setting such as India with limited price information. Based on the empirical evidence, the study plans to draw the spatial price map of India with different colours denoting states and districts with varying level of spatial prices.Design/methodology/approachThis study shows that a procedure proposed by Lewbel (1989), based on the idea by Barten (1964) that household composition changes have “quasi-price effects”, can be used to estimate spatial prices in the absence of information on regional prices.FindingsThe evidence on spatial price differences in India, which is the most comprehensive to date because it goes down to district level, shows that the proposed procedure has considerable potential in future applications on other data sets with limited price information. The policy importance of the results is underlined by the sensitivity of the demand elasticities to the inclusion/omission of spatial price variation.Research limitations/implicationsThe study uses “pseudo unit values” based on household composition and demographic effects on demand as proxy for the missing price information. While the work of Atella et al. (2004) suggests that such proxies are accurate representations of true prices, nevertheless, they are proxies and the results should be treated with caution.Practical implicationsThe evidence on spatial prices in India that point to a high degree of price heterogeneity between regions implies that welfare applications such as income distributional and poverty studies must take account of the price heterogeneity within the country. The implications extend beyond India to cross-country exercises such as the purchasing power parity calculations undertaken by the International Comparison Project.Originality/valueThis is one of the first studies that provide evidence on spatial price heterogeneity within a country without requiring regional price information. Methodologically, the paper builds on the suggestion of Lewbel (RES, 1989) in showing how the demographic effects on household expenditure pattern can be used to estimate spatial prices. The value of the contribution lies in the use that the estimated spatial prices can be put to in calculating inequality and poverty rates and in standard of living comparisons between regions in the country.

中文翻译：

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使用伪单位值绘制的印度空间价格图

目的本研究旨在应用一种建议的方法来计算价格信息有限的异质国家环境中的空间价格，例如印度。基于经验证据，该研究计划绘制印度的空间价格图，用不同的颜色表示具有不同空间价格水平的州和地区。设计/方法/方法本研究表明，Lewbel (1989) 提出的程序，基于Barten (1964) 提出的家庭构成变化具有“准价格效应”的想法，可用于在缺乏区域价格信息的情况下估计空间价格。日期，因为它下降到地区级别，表明所提出的程序在价格信息有限的其他数据集的未来应用中具有相当大的潜力。需求弹性对空间价格变化的包含/省略的敏感性强调了结果的政策重要性。研究限制/影响该研究使用基于家庭组成和人口对需求的影响的“伪单位值”作为缺失的代理价格信息。虽然 Atella 等人的工作。(2004) 认为这样的代理是真实价格的准确表示，然而，它们是代理，结果应该谨慎对待。实际意义 印度空间价格的证据表明区域之间存在高度的价格异质性，这意味着收入分配和贫困研究等福利应用必须考虑该国内部的价格异质性。其影响不仅限于印度，还延伸到跨国活动，例如国际比较项目进行的购买力平价计算。原创性/价值这是在不需要区域价格信息的情况下提供一个国家内空间价格异质性证据的首批研究之一。在方法论上，本文建立在 Lewbel (RES, 1989) 的建议之上，展示了如何使用人口对家庭支出模式的影响来估计空间价格。