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Craigslist & the Economy:Predicting Unemployment and Foreclosure Trends from Online Classified Advertisements

Module by: Ziyad Aljarboua. E-mail the author

Summary: In this paper we present findings of an experimental study of Craigslist.org involving nearly 4 million raw online classified advertisements to infer key economic indicators. First, we investigate the potential of using Craigslist information to predict the state of the national and local economy by analyzing user behavior and posting trends in some key categories. We show that the number of posts for jobs available/wanted reflects the actual trends reported by the U.S. Bureau of Labor Statistics. We examine the potential of predicting unemployment and home foreclosure rates from online classified advertisements in geographically localized peer production communities. We show that there is a strong correlation between the number of houses posted for sale, the number of jobs available/wanted and the actual state of the local and national economy. Finally, we analyze job posts in 32 categories and day to day changes and conclude the “recession proof jobs” and jobs highly affected by the recent economic meltdown.

see full paper at

http://tinyurl.com/ziyad-aljarboua

Ziyad Aljarboua

Harvard University

aljarb(.at.)fas.harvard.edu

Introduction

Craigslist is a unique type of peer production systems where users collectively contribute to localized online communities rather than a central location. Craigslist enables users to post online classified advertisements in several categories including housing, jobs, resumes, services, personals and forums where users can discuss various topics. According to alexa.com, craigslist.org received over 9 billion page requests from over 30 million unique visitors making it one of the most popular websites worldwide. Each month, over 30 million new classified advertisements and 2 million new job listings are posted [1]. As of December 2008, Craigslist.org has a worldwide traffic rank of 38 and over 9,500 sites linking to it [2]. The motivation for this experimental study is the recent global economic downturn that began in the early months of 2008. Although the U.S. has been in a recession for over a year now, the National Bureau of Economic Research only declared that the United States is officially in a recession in December 1, 2008. The basis for this experiment stems from two major observations. First: the realization that the 2008 housing bubble fueled by the increased foreclosure rates and declining housing prices is the main cause behind the 2008 economic crisis. Second: the fact that unemployment rate is a strong measure of the state of the economy. Our underlying assumption is that people reveal their wants, needs and financial situations through their posts on Craigslist. This paper demonstrates how online peer production systems could potentially be used to predict the state of the local and national economy by tracking key measures such as house sales and jobs. The sharp rise of the E-labor market presents the internet as a viable tool to gauge the rate of unemployment. A 2001 survey by the Canadian Public Service Commission showed that 78% of public service external recruits used the internet for their job search [3]. And in the U.S., over 8.64% of the population engages in online job search [4]. While this percentage might seem small, it is still higher that the highest national unemployment rate during the past decade of 6.7% [5]. In this paper, we use collected data from Craigslist to analyze key economic measures, mainly: home foreclosure and unemployment rates. We show that posts for jobs available/wanted and house sale are directly related to unemployment and foreclosure trends respectively. We show that the number of posts per day in several key categories reflects the real economics situations and the actual trends. By analyzing job categories separately, we observe the impact of the recent economic downturn on specific professions and conclude jobs that are “recession proof.”

continue paper here

http://tinyurl.com/ziyad-aljarboua

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