A Dutch disease approach into the premature deindustrialization - Çakır, Muhammet Sait (Graduate School, 2022)
We explore the main causes and consequences of the premature deindustrialization phenomena. We argue that local currency overvaluations mainly associated with a surge in capital inflows into the emerging market economies following the deregulation of their capital accounts severely hurt the output share of manufacturing industry. First, we empirically establish a causal link from capital flows to local overvaluations. According to the two-way error component model which controls for the full set of country and time fixed effects, a surge in capital flows by one standard deviation is associated with an overvaluation of 1.67 percent. To address the possible endogeneity between capital flows and real exchange rate, we run two-variate first-order panel vector autoregressive model since the feedback effects from overvaluation to net financial inflows might introduce a bias into the fixed effect estimation. When we isolate the effect of positive capital inflow shock of one standard deviation by the Cholesky decomposition, we find that it is statistically significantly associated with an immediate overvaluation in real terms with 95 percent confidence level. Then we construct our baseline regression model. Applying the second generation estimators allowing for cross-section dependency (Augmented Mean Group and Common Correlated Effects Mean Group), we run a panel data regression model based on a sample of 39 developing countries in Latin America, Sub-Saharan Africa, East Asia, North America, and Europe from 1960 to 2017. We find that an overvaluation of 50 percent which corresponds approximately to one and half standard deviations is associated with a contraction of manufacturing output share as high as 1,25 percent over the five year period. With the turn of new century, the developing countries also experienced a massive deindustrialization by shedding manufacturing value-added as large as 1.24% of national income. Moreover, the evidence suggests that the relationship between real exchange misalignments and the manufacturing share in output might be nonlinear so that the manufacturing competencies which have been eroded by local currency overvaluations in real terms cannot simply be brought back during the undervaluation periods. We also show that the baseline regression results are robust to different data sets, alternative real exchange rate/deindustrialization measurements, and dynamic model specifications which allow us to treat the real exchange rate as endogenous variable to address any potential concern regarding the simultaneity bias. As a further robustness check on our findings, we empirically examine the effects of supply chain disruptions, inequality shocks, and institutional innovations on the path of industrialization in developing countries by running a panel vector autoregressive model. We found that deterioration in income distribution unequivocally harms the developing countries' bid for industrialization while better institutions proxied by an improvement regulatory quality invariably foster it. On the other hand, the effects of supply chain disruptions on the pace of industrialization follow a nonlinear path, showing the great resilience of local industries in absorbing imported input bottlenecks through intermediate input import substitution. We also provide evidence that backward participation into GVCs and regulatory quality do not mutually Granger-cause each other, and suggest that the well-established link from better governance to GVCs may be missing in the developing country case. Based on these empirical findings, the need for a comprehensive industrial policy along with a firm use of capital controls and macroprudential measures given a robust institutional framework comes out as the main policy implication of our work, and they are duly discussed in light of recent developments in the literature.
Erken sanayisizleşmeye Hollanda hastalığı yaklaşımı
Thesis(Ph.D.) -- Istanbul Technical University, Graduate School, 2022
Keywords: panel data models; panel veri modelleri; deindustrialization; sanayisizleşme; structural change; yapısal değişme