Reassessment of the Todaro paradox: an extended panel data analysis on developing countries

The concept of migration encompasses different perspectives. Internal migration refers to mobility within the borders of a nation (Puhani, 2001), whereas external migration refers to mobility between settlements in two or more countries (Bell et al., 2002). An individual who migrates from one country to another for employment purposes is considered an immigrant (Gimeno-Feliu et al., 2019; Jean, Jimenez, 2011; Kemnitz, 2003; Wong, 1991). Ravenstein studied the behavior patterns of individuals in relation to migration and noted that the movements of immigrants tend to be short-distance and directed towards large commercial and industrial centers (Ravenstein, 1889). As a result, migration from areas close to big cities is on the rise and has become a popular destination for immigrants seeking employment. On the other hand, residents of urban areas tend to migrate less frequently compared to their rural counterparts, leading to a higher rate of rural-tourban migration (Ravenstein, 1889). Migration that involves leaving one’s country for a different region for employment purposes can result in differences between the sending and receiving regions in terms of their economic and social characteristics (Castles, 2000) . The issue of employment is crucial in this context. Many studies have shown that unemployment is a major motivator for migration

(Herzog, Schlottmann, 1984; Kingma, 2007; Potts, Mutambirwa, 1990; Zhang, Song, 2003). Employment, as an economic concept, refers to the use of production factors for the purpose of generating income. In addressing the problem of unemployment, countries implement various policies and strategies.

Policies aimed at enhancing employment in cities can lead to migration from rural to urban areas, particularly in developing countries. Todaro and Harris modeled the factors that drive rural-tourban migration in developing nations (Todaro, 1969; Harris, Todaro, 1970). In their model, the determining factors are wage differences between rural and urban areas and employment opportunities in cities. As long as expected urban wages, adjusted by the probability of finding a job, are higher than rural wages, migration from rural to urban areas will persist. In developing countries, it takes place in two stages. Initially, migrants are unable to secure formal sector employment due to a lack of qualifications, but they find work in the informal sector. In the second stage, they switch to formal sector employment. As a result, unemployment is both a cause and a consequence of migration and will persist as long as there are wage and employment disparities between rural and urban regions (Harris, Todaro, 1970; Todaro, 1969). The duration of time required to secure formal sector employment and the availability of employment opportunities are important factors in triggering migration (Todaro, 1969). Todaro introduced the concept of the “Todaro Paradox”, which suggests that the positive effect of increasing employment opportunities in urban areas on unemployment is offset by the negative effect of rural-to-urban migration. Investments aimed at reducing urban unemployment may lead to higher unemployment, emphasizing the importance of rural development in addressing the issue (Todaro, 1976).

On the other hand, considering Purchasing Power Parity (PPP), which represents a rate of change that equalizes the purchasing power of different currencies by removing price level disparities between countries is crucial for the analysis of the Todaro paradox1. The study of PPP began several decades ago, with the most well-known method of calculation being the Geary-Khamis dollar. This method, introduced by Roy C. Geary in 1958 and developed by Salem H. Khamis in the early 1970s (Brunt, Fidalgo, 2018), combines PPP and international average prices of goods. The calculation of PPP in the USA is based on the years 1990 or 2000, and international comparisons of per capita income in Geary-Khamis dollars provide a more meaningful comparison of standard of living than per capita income at current prices (Nordhaus, 2007). The US dollar serves as the common currency in these calculations (Dornbusch, 1985).

The Todaro Paradox and purchasing power parity are two related economic concepts. The Todaro Paradox is caused by the fact that, despite high levels of urban unemployment, people still migrate from rural to urban areas in search of work. This contradicts the classical theory of migration, which states that people should only move if there are more job opportunities in the destination location (Haas et al., 2019). PPP, on the other hand, is a theory that states that the exchange rate between two currencies is equal to the ratio of the prices of a basket of goods in each country (Samuelson, 1964). In other words, PPP states that the same goods should cost the same amount in different countries after adjusting for exchange rates. The relationship between the Todaro Paradox and PPP lies in the fact that PPP is often used to measure the purchasing power of different currencies in different countries. When PPP is applied to the Todaro Paradox, it becomes clear that people are moving to urban areas not just because of the availability of jobs, but also because they believe that their purchasing power will be higher in the city, even if they are unemployed. PPP helps to shed light on the motivations behind migration in the context of the Todaro Paradox, and can help economists better understand the forces driving rural-urban migration.

In this study, the “Price level ratio of PPP conversion factor (GDP) to market exchange rate” is employed as a variable to test the correlation and causality between this factor and the rate of rural-urban migration. This relationship has not been previously examined in the existing literature on the subject. The study aims to contribute to the field by incorporating a unique variable and conducting econometric analysis using three different techniques: Fixed Effect (FE), Random Effect (RE) and Full Modified Ordinary Least Square (FMOLS).

Several propositions motivated us to conduct this investigation.

First, we aim to address the socio-economic problems associated with migration, which are crucial for development, within the context of the Todaro Paradox. The purpose of the paper is to emphasize the importance of this critical topic and to consider comprehensively its implications, which have been overlooked by the empirical literature.

Second, the Todaro Paradox explains why people in developing countries migrate from rural areas to urban areas despite worsening economic conditions in the latter. Focusing on the Todaro Paradox by using the correct variables can provide insights into the motivations behind rural-urban migration and the push and pull factors that influence this phenomenon.

Third, policymakers can better target interventions aimed at reducing rural-urban migration and promoting sustainable development in developing countries by understanding the Todaro Paradox.

Fourth, rural-urban migration can have both positive and negative effects on the development of a country. By studying the Todaro Paradox, researchers can better understand the results of rural-to-urban migration and identify ways to mitigate its negative effects while enhancing its positive effects.

Our contributions to the literature can be divided into two folds. First, we use the price level ratio of the PPP conversion factor (GDP) to the market exchange rate since the higher the PPP of a country, the lower the rate of rural-urban migration is expected. By using one extra variable (unemployment), we test the Todaro Paradox. This combination of variables allows us to draw more meaningful conclusions and have the potential to reveal new insights into economic literature.

Second, the FE, RE and FMOLS methods allow for a more comprehensive and nuanced examination of the relationship between the price level ratio of PPP conversion factor and other variables related to rural-urban migration, leading to more robust results and a better understanding of the underlying causal relationships. Moreover, these techniques allow for the control of potential omitted variable bias, cross-sectional dependence, and endogeneity.