Ekonometride Güncel Yöntemler ve Uygulamalar
Türkiye’de Cari İşlemler Dengesi ve Sektörel Büyüme İlişkisi
Nebiye Yamak, Serkan SamutAmpirik literatür cari işlemler dengesi ile ekonomik büyüme oranı arasındaki “nedensel ilişkileri” araştıran çalışma sayısı itibariyle oldukça zengindir. Mevcut çalışmalar içinde Türkiye örneğini de analiz eden çalışmalar bir hayli fazladır. Ne var ki, bu çalışmaların tamamında cari işlemler dengesi ile ilişkilendiren büyüme oranı “genel” ekonomik büyüme oranıdır. Literatürdeki genel bulgu, cari işlemler dengesi ile genel ekonomik büyüme oranın birbirlerini besledikleri yönündedir. Ancak burada akla gelen soru, acaba böyle bir bulguda terkip hatası var mıdır? Diğer bir ifadeyle böyle bir bulguda acaba toplulaştırma sapması var mıdır? Dolayısıyla bu çalışmadaki temel amaç cari işlemler dengesi ile ekonomik büyüme oranı arasındaki olası nedensel ilişkileri sektörel bazda araştırmak ve yukarıdaki soruyu cevaplandırmaktır. Ayrıca Türkiye özelinde cari açıkla yüksek derecede ilişkili ve sorumlu olan sektörleri belirlemek de mevcut çalışmanın bir diğer amacını oluşturmaktadır. Ele alınan dönem 1998:1-2018:3 arasını kapsamaktadır. Veriler üçer aylık olup mevsimsellikten X-12 yöntemiyle arındırılmıştır. Cari işlemler dengesinin ilişkilendirildiği sektörler sanayi, imalat, inşaat, hizmetler, finans-sigorta ve tarım sektörüdür. Çalışmada serilerin bireysel ve birlikteki istatistiksel özelliklerine uygun olarak VAR yöntemi kullanılmıştır. VAR bulgularına göre genel toplamda geçerli olan sektörel bazda geçerli olmamıştır. Genel ekonomik büyüme oranın kullanıldığı analize göre, cari işlemler dengesi ile ekonomik büyüme oranı arasında birbirlerini besleyen bir ilişki mevcuttur. Ancak sektörel büyüme oranlarının kullanıldığı analiz bulgularına göre, sadece büyüme oranı cari işlemler dengesini beslemektedir. Tersi doğru değildir.
Current Account Balance–Sectoral Growth Relationship in Turkey
Nebiye Yamak, Serkan SamutA strong consensus exists in international economic literature that economic growth is one of the main causes of current account deficits. The deficit of structural savings, particularly in developing countries, naturally leads to savings and investment imbalances, which naturally leads to a deficit in the current account balance. In other words, it is theoretically expected that current account balance will have a higher deficit than other periods in periods of high economic growth. In contrast, current account deficit is likely to close or even carry a surplus, as foreign savings are not much needed during periods of low economic growth. As a result, it is a theoretical assumption that a negative relationship exists between current account balance and economic growth.
Current literature is rich in the number of studies investigating “causal relationships” between current account balance and economic growth; however, in all of the existing studies, the growth rate associated with current account balance is the “overall” economic growth rate (Aristovnik, 2007; Lebe et al, 2009; Morsy, 2014). The general finding in the literature is that current account balance and general economic growth rate feed each other. A question that comes to mind here is if a fallacy of composition is inherent in such findings? There are two possible causes of a fallacy of composition that may occur in causal analyses with aggregated data; one is theoretical, and the other is statistical. In particular, it is expected that the sectors in which investments can be financed only by means of external savings can have a strong causal relationship with current account deficit.
Although the sum of the economy-wide sectoral savings investment imbalance will reveal the total investment savings imbalance, the causal relationships in the aggregate may differ from the sectoral relations. In other words, the internationality index of each sector that contributes to the economic growth rate differs. Some sectors are directly related to the balance of payments due to their activities, whereas others are only indirectly involved. Therefore, the results of causality analysis that will be realized by pooling the sectors that theoretically interact with the balance of payments at different levels will not reflect reality and will mislead policymakers and practitioners. In addition, statistically inefficient and biased results can be obtained with aggregated data (Andreou, et al., 2010). Thus, Pesaran et al. (1989) showed that the findings of analyses using aggregated variables and non-aggregated variables may differ from one another. This is because aggregation causes information in the non-aggregated series to either disappear or alters its distribution (Marcellino, 1999; Götz et al., 2015).
The main purpose of this study is to investigate the possible causal relationships between current account balance and economic growth rate on a sectoral basis and to address the above question regarding a potential fallacy of composition. The period investigated covers 1998Q1–2018Q3. Data were quarterly and seasonally adjusted using the X-12 method. The sectors to which current account balance is related are industry, manufacturing, construction, services, finance-insurance, and agriculture. In this study, the VAR method was used in accordance with the statistical characteristics of the series.
In the VAR analysis using aggregated data, a two-way causality relationship was determined between the current account deficit and economic growth rate. While the economic growth rate Granger causes the current account deficit, the current account deficit causes the economic growth rate. The two-way causal relationship revealed between the two series was similar to the findings in the literature. However, when sectoral growth rates are used instead of economic growth, the results confirm the claim of a fallacy of composition, as no causal relationship was found from the current account deficit to the growth rate for any sector. A oneway causal relationship from sectoral economic growth to current account deficit was found for the industry, manufacturing, construction, and services sectors. As expected, the strongest relationship among these sectors was in the industrial sector. No causal relationship was found in the financial-insurance and agricultural sectors. Although this finding is understandable for the agricultural sector, it was unexpected for the finance and insurance sectors.
