Determinants of Construction Sector Activity in Turkey: A Vector Autoregression Approach

Abstract

<p>This study analyzes the effects of some major macroeconomic variables on construction sector activity in Turkey by employing a Vector Autoregression (VAR) model from 1990<em>Q</em>1 to 2010<em>Q</em>3. The 4-variable VAR model includes the log of construction sector activity (<em>COACT</em>), the log of real gross domestic product (<em>RGDP</em>), weighted averages of 12-month interest rate on deposit (<em>INT</em>) and the log of banking sector total domestic credits (<em>CRE</em>). According to VAR model impulse response analysis, the sector booms related to a positive one standard deviation shock in <em>RGDP</em>. Thereby, the importance of maintaining economic stabilization is revealed since economic contractions may affect the sector negatively. In addition to this finding, impulse response analysis indicates that a positive one standard deviation shock in<em> INT </em>deteriorates the construction sector activity.<em> </em>Therefore, interest rates should be kept low by the coordination of monetary and fiscal policy. Moreover, impulse response analysis results emphasize that credit supply and demand should be equalized for minimizing default risk. On the other hand, forecast error variance decomposition (FEVD) analysis infers the importance of real gross domestic product, weighted averages of 12-month interest rate on deposit and banking sector total domestic credits in determining construction sector activity.</p

Nexus between construction sector and economic indicators for Turkey and European Union evidenced by panel data analysis

“…Countries with long-run estimates show unexpected results about negative estimates between the CS and GDP and vice versa . This result contrasted with the studies of Kargi (2010) and Ozcelebi (2011). The discrepancy may result from the governmental controls over most CS and related activities: facilities and services like social and residential buildings, hospitals, football stadiums and parks and other projects, resulting in poor-income generators.…”

“…The results show a negative effect of interest rate on the CS and show a negative effect of CS on the industry sector and vice versa, while previous studies in different countries show positive effect of CS on the industry (Akintoye and Skitmore, 1994; Ozcelebi, 2011; Ilhan and Yaman, 2011). The investment shows positive regression in the CS and in industry sector, which conforms to the previous studies' results (Ozcelebi, 2011; Bielsa and Duarte, 2011). The regression results based on the hypothesis of the study introduced that the GDP, CS and investment have a positive relationship that leads to growth and the interest rate shows a negative relationship with CS which leads to a negative impact on the growth of the sector, potentially impacting on the economic growth.…”

“…However, the difference in approach to the analysis presented varied results. Some studies show a positive impact (Kargi, 2010; Ozcelebi, 2011; Ozkan et al. , 2012) of the CS on the GDP of Turkey (and vice versa ) and EU, while some other studies show no relationship between them (Gundes, 2011; Gunluk-Senesen et al.…”

“…However, the difference in approach to the analysis presented varied results. Some studies show a positive impact (Kargi, 2010;Ozcelebi, 2011;Ozkan et al, 2012) of the CS on the GDP of Turkey (and vice versa) and EU, while some other studies show no relationship between them (Gundes, 2011;Gunluk-Senesen et al, 2012;S ¸ahin et al, 2015). While GDP, GNP and some other economic indicators were studied, no attempt was made earlier to analyze interest rate, credits and composition of overall taxation or changes in taxation on CS and GDP growth, using regression, cointegration and causality methods.…”

Soft Computation Vector Autoregressive Neural Network (VAR-NN) GUI-Based

“…The autoregressive vector model is a multivariate time series method that can explain endogenous variables from past data of the variable. Vector Autoregressive (VAR) is an econometric method that is useful for testing the relationships between variables in a model that has a dynamic impact [12]. If there is a simultaneity between a set of variables, then it should be treated in a fair condition (Equal Footing), ie there is no priority difference between endogenous and exogenous variables.…”