PurposeThe paper aims to identify the determinants of employment in Pakistan. In light of the jobless growth Pakistan has experienced starting from 2000, this is a valid concern. The paper discusses the structural relationship between employment and growth in Pakistan and analyzes it empirically within an economic geography framework.Design/methodology/approachThe paper applies a Logit regression analysis to data from Pakistan Social and Living Standard Measurement Survey for the years 2010, 2012 and 2014. While this survey is published annually, the paper uses data at the district level, which is available only every alternate year. Data are collected at the individual level and can be mapped back to the household level. Each wave of data covers at least 70,000 households. The survey provides data on employment status, health, education, sanitation, economic situation and asset ownership. The analysis is conducted using Stata. The paper uses computer vision to present and trace changing employment patterns in Pakistan over time. To do so, the paper uses MATLAB. The data are transformed to KMV format and the plotting is done using Google Earth.FindingsThe paper shows how household characteristics affect the odds of employment in Pakistan, finding evidence of provincial disparities. Moreover, the paper shows that non-wage income from assets reduces the odds of being employed. The paper identifies the various income thresholds for the five income sources examined to have an impact on the odds of employment.Originality/valueThe novelty of this research is the identification of the determinants of employment in Pakistan and their analysis from the perspective of economic geography. This paper should be useful for policymakers and international financial organizations concerned with structural change in Pakistan.

中文翻译：

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确定在巴基斯坦的就业机会

目的本文旨在确定巴基斯坦就业的决定因素。鉴于巴基斯坦自 2000 年以来经历的失业增长，这是一个合理的担忧。本文讨论了巴基斯坦就业与增长之间的结构性关系，并在经济地理框架内对其进行了实证分析。设计/方法/方法本文将 Logit 回归分析应用于 2010 年、2012 年和 2012 年巴基斯坦社会和生活水平测量调查的数据2014. 虽然这项调查每年发布一次，但该论文使用地区级别的数据，该数据仅每隔一年提供一次。数据是在个人层面收集的，并且可以映射回家庭层面。每一波数据至少覆盖了 70,000 个家庭。该调查提供了有关就业状况、健康、教育、卫生、经济状况和资产所有权。使用Stata进行分析。该论文使用计算机视觉来呈现和追踪巴基斯坦随时间变化的就业模式。为此，本文使用 MATLAB。将数据转换为 KMV 格式，并使用 Google 地球进行绘图。发现该论文显示了家庭特征如何影响巴基斯坦的就业几率，并找到了省级差异的证据。此外，该论文表明，来自资产的非工资收入降低了被雇用的几率。本文确定了五种收入来源的各种收入门槛，以影响就业几率。原创性/价值本研究的新颖之处在于确定了巴基斯坦就业的决定因素，并从经济地理学的角度对其进行了分析。