Assessing the impact of recent Venezuelan immigration on housing rents in Colombia

ABSTRACT

The economic and social crisis faced by Venezuela since 2013 has led to a massive migration of its population to neighbouring countries, with Colombia being the nation that has been the most impacted. This paper estimates the impact of Venezuelan immigration on housing rents in Colombia’s main cities. Using a repeated cross-section data of Colombian households between 2013 and 2019, along with an instrumental variables approach, this study finds that a 1% increase in the proportion of Venezuelan immigrants to residents in the main cities in Colombia raises housing rents, on average, by about 1.25%.

KEYWORDS:

• immigration
• housing rents
• developing countries
• Colombia
• Venezuela

JEL:

• F22
• R21
• R31

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1 According to the National Administrative Department of Statistics, the 13 large cities and their metropolitan areas are: Bogotá; Medellín y Valle de Aburrá; Cali y Yumbo; Barranquilla y Soledad; Bucaramanga, Floridablanca, Girón, Piedecuesta; Manizales y Villamaría; Pasto; Pereira, Dosquebradas y La Virginia; Ibagué; Cúcuta, Villa del Rosario, Los Patios y El Zulia; Villavicencio; Montería; and Cartagena.

2 For example, there are around 700 observations for which their imputed housing rents equal imputed minimum housing price.

3 Since we did not have information about temperature for Manizales y Villamaría and Montería and precipitation for Manizales y Villamaría, Montería and Cúcuta, we employed an ordinary kriging technique to predict these missing values.

4 Housing rents are also preferred over household prices because they are better approximations of the dwelling cost for tenants (Moretti, 2013). In addition, rent is a more plausible measurement of household values because it incorporates only the value paid during the period that an individual lives in a particular dwelling (Winters, 2009). While the survey gathers monthly information on housing rents, it also collects information on international immigration for each month. This allows us to compute the annual inflow of immigrants from Venezuela to Colombia to quantify the effect of immigration share on monthly housing rents.

5 Although it is common to estimate clustered standard errors when using data grouped by spatial units, our data set contains information for only 13 cities, which are significantly fewer than the 42 clusters recommended to avoid bias issues, therefore we decided not to use standard errors clustered by city (Angrist & Pischke, 2009).

6 As stressed by Jaeger et al. (2018), past levels of immigration usually display a high correlation with the current level of immigration (in our case, 0.7 for the first instrument, and 0.9 for the second instrument), producing a too strong instrumental variable. This empirical issue casts serious doubt on the ability of the instrument to meet the exclusion restriction. Given this concern, we also test the robustness of the IV estimates by relaxing the exclusion restriction. For this analysis, see the subsection ‘Testing the quality of the instruments’.

Additional information

Funding

The authors acknowledge financial support from CONICYT/Chilean Fondecyt 11170018 ‘City differences in the return to schooling’.