Abstract
We exploit the regional variation in the unexpected (or forced) inflow of Syrian refugees as a natural experiment to estimate the impact of immigration on consumer prices in Turkey. Using a difference-in-differences strategy and a comprehensive data set on the regional prices of CPI items, we find that general level of consumer prices has declined by approximately 2.5 % due to immigration. Prices of goods and services have declined in similar magnitudes. We highlight that the channel through which the price declines take place is the informal labor market. Syrian refugees supply inexpensive informal labor and, thus, substitute the informal native workers especially in informal-labor intensive sectors. We document that prices in these sectors have fallen by around 4 %, while the prices in the formal labor-intensive sectors have almost remained unchanged. Increase in the supply of informal immigrant workers generates labor cost advantages and keeps prices lower in the informal labor-intensive sectors.
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Notes
This figure includes the estimated number of unregistered refugees. For the latest numbers and more detailed statistical information about the Syrian refugee crisis, see the United Nations website http://data.unhcr.org/syrianrefugees/regional.php.
See Tumen (2015) for the use of natural experiments in migration research.
See AFAD (2013) for the details of the survey results. There are 20 accommodation centers (camps) in 10 cities in Turkey. The accommodation centers are located in Adana, Adiyaman, Hatay, Gaziantep, Kahramanmaras, Kilis, Malatya, Mardin, Osmaniye, and Sanliurfa. Most of the Syrian refugees have been living in these or the neighboring cities. Although, there is a significant number of refugees in the other regions of Turkey, such as Istanbul (2.2 %) and Konya (2.3 %), their number is small relative to the population in these regions. Based on the refugee over population ratios, we observe that the refugees have been quite densely located in Kilis (38.1 %), Sanliurfa (9.4 %), Gaziantep (11.9 %), Hatay (12.6 %), Osmaniye (2.4 %), and Mardin (9.0 %). See Ceritoglu et al. (2015) for more details.
Unlike most of the Western countries, the term “immigration” is relatively new for Turkey. Except the case for a much smaller number of refugees received during the Gulf War and the case for expatriates from Bulgaria, Turkey has not been exposed to any consistent immigrant flows in the post-World War II era. Some countries deal with immigration issues and set long-term policies by establishing ministries with exclusive focus on immigrants. In this sense, Turkey is relatively inexperienced about the immigration issues/policies, which translates into the lack of any legal arrangements for providing work permit to immigrants. Although there is some effort to rehabilitate the legal status of immigrants, it will likely take some time before these efforts are finalized as the Syrian Conflict also involves domestic/international politics as well as the international coordination issues.
See also Zachariadis (2011).
There are several other papers focusing on other outcomes exploiting similar natural experiments. Gould et al. (2009) investigate the impact of immigration on long-term educational outcomes. Paserman (2013) estimates the effect of immigration on worker productivity. Maystadt and Verwimp (2014) analyze the welfare effects of forced immigration. Saarela and Finnas (2009) study the long-term effects of forced immigration on mortality rates.
See Fig. 2 for the exact location of these cities on the map.
For more contextual details, see the documentation posted on the website (https://www.afad.gov.tr/en/Index.aspx) of the Turkish Disaster and Emergency Management Presidency (AFAD).
Another concern might be related to the existence of “daily migration” of workers between regions. We do not have data to convert this concern into a directly measurable variable, but our observation is that work-oriented daily migration is not a common practice in Turkey. Moreover, our regional classification is broad, i.e., the NUTS2-level classification places several cities in each region. In addition, the distances between the cities/regions are quite large. So, the existence of any systematic daily migration pattern (to the extent that can contaminate our estimates) is a highly unlikely scenario.
To have an idea about the goodness of the control group, see Ceritoglu et al. (2015) for detailed information on both the demographic characteristics of the natives residing in the control versus treatment areas and the development/labor market indicators of the control versus treatment regions.
It is well-known that the standard errors of a difference-in-differences estimator may be underestimated (and, therefore, may lead to overestimated statistical significance) if the potential serial correlation issues are not appropriately controlled for [see, e.g., Moulton (1986) and Mullainathan et al. (2004)]. To avoid this problem, we clustered the standard errors by month, item, region, region-month, item-month, and item-region. We also tried the block bootstrap method. Among all of these alternatives, clustering the standard errors by the month of observation gave us the most conservative standard errors—consistently across specifications. Accordingly, we clustered the standard errors by the month of observation.
We list the basic and luxury food items below Table 9. The constant terms in the regressions demonstrate the large price differentials between basic versus luxury food items.
The result that prices of basic foods decline much faster than the prices of luxury foods may have an alternative interpretation. Immigrant flows may affect demand conditions both through shifting the level of aggregate demand and generating a change in the composition of aggregate demand. If immigrants have lower opportunity cost of time than natives, then they may search for low prices more intensively than natives. Moreover, the price search activity of immigrants may be more intensive for basic food items than luxury food items. As a result, a price-search mechanism may also be operating in the background. It should be noted that basic food items are likely produced via a more informal labor-intensive technology than luxury food items. So, our findings along the basic versus luxury food divide can also be interpreted as an evidence favoring the informal labor market channel that we propose in this paper. But there is no easy way of separately identifying these two potential forces given the data at hand.
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Acknowledgments
We thank the seminar participants at the Central Bank of the Republic of Turkey, the participants of the 2015 IZA/World Bank Conference on Employment and Development in Bonn, the European Economic Association 2015 Annual Meeting in Mannheim, and the American Economic Association 2016 Annual Meeting in San Francisco for useful comments. We are particularly grateful to Robert Shiller, Klaus Zimmermann (the editor), and three anonymous referees for extremely helpful suggestions. The views expressed here are of our own and do not necessarily reflect those of the Central Bank of the Republic of Turkey. All errors are ours.
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Responsible editor: Klaus F. Zimmermann
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Balkan, B., Tumen, S. Immigration and prices: quasi-experimental evidence from Syrian refugees in Turkey. J Popul Econ 29, 657–686 (2016). https://doi.org/10.1007/s00148-016-0583-2
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DOI: https://doi.org/10.1007/s00148-016-0583-2