YP CİNSİNDEN BORÇLANMA, İSTİHDAM VE FİRMA BÜYÜMESİ

Year 2023, , 516 - 526, 29.09.2023

Huzeyfe Torun

https://doi.org/10.17130/ijmeb.1349720

Abstract

Bu çalışmada Yabancı Para (YP) cinsinden borçlanmanın firma büyümesindeki rolü incelenmiştir. Firma seviyesinde detaylı bir veri setinde genişletilmiş tam eşleme (coarsened exact matching) yöntemi uygulanarak ölçek, karlılık, maddi duran varlık yoğunluğu ve kullanılan kredi tutarı açısından benzer olan fakat kullanılan kredinin kur cinsi farklı olan firmaları tespit edilmektedir. Ardından panel veri sabit etkiler modelleri kullanılarak YP cinsinden kredilerin firma büyümesindeki etkisi incelenmektedir. Diğer bir ifadeyle, daha yüksek YP cinsinden kredi payına sahip firmaların daha iyi firma sonuçlarına sahip olup olmadığını analiz ediyorum. Sonuçlar YP kredilerin firma büyümesi üzerindeki rolünün son yıllarda azaldığını göstermektedir. 2017 yılına kadar olan süreçte YP kredi kullanan firmalar benzer miktarda TL kredi kullanan firmalara göre daha yüksek büyüme oranına sahipken 2017 sonrası dönemde bu ilişkinin değiştiği görülmektedir.

Keywords

Firma büyümesi, İstihdam, Yabancı para borç

FX BORROWING, EMPLOYMENT AND FIRM GROWTH

Abstract

Matching (CEM) methodology using a rich firm-level dataset in order to find counterpart firms that are similar in terms of amount of loans, size, profitability and tangible asset but different in currency of the loan used. Then I use panel data fixed effect regressions to measure the impact of FX loan on firm employment and sales growth compared to TL loan. More specifically, analyze whether firms with higher FX denominated credit share have better firm outcome or not. The results point to diminishing impact of the FX loans on firm growth in recent years. While the firms borrowed in FX have higher growth rate compared to TL borrowed firms until 2017, there is no significant difference in firm employment growth or sales growth performance between FX-indebted firms and TL-indebted firms.

Keywords

Firm growth, Emplyment, FX Loan

Thanks

I would like to thank Ahmet Duhan Yassa for his valuable comments and help in understanding some of the details of the data set.

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