Inflation, Output Growth, and Stabilization in Turkey, 1980-2002

Using a dynamic aggregate supply and aggregate demand model with imperfect capital mobility and structural VARs, we decompose inflation and output movements into those attributable to terms of trade, supply, balance-of-payments, fiscal, and monetary shocks. Empirical results show that terms of trade shocks have a significant negative effect on inflation in the short run. In the long run, monetary, and balance of payments shocks dominate while budget deficits play a limited role in the inflationary process. Demand shocks have limited effects on output movements; output is mostly driven by terms of trade and supply shocks. The results highlight the importance of a credible disinflation program and structural reform that restrain discretionary aggregate demand policies.Causes and effects of inflation, inflation theories, stabilization policy, theory of aggregate supply and aggregate demand, time series models, Turkish economy

Critical Values of the Empirical F-Distribution for Threshold Autoregressive and Momentum Threshold Autoregressive Models

This paper provides exact (finite-sample) test critical values for carrying out tests of no cointegration versus some forms of nonlinear (threshold autoregressive) cointegration. The nonlinear models, which include threshold autoregressive and momentum threshold autoregressive behavior of deviations from long-run equilibrium, are easier to evaluate with the aid of the reported critical values. The results cover a variety of practical situations, with varying sample sizes, lag lengths, and number of time series

Return and risk spillovers between the ESG global index and stock markets: Evidence from time and frequency analysis

In this paper, we examine comovements between stock market returns and investments that take into account Environmental, Social, and Governance (ESG) factors by studying the interconnections between the two returns in time and frequency space. We study interdependencies between the conventional stock market and ESG stocks using daily data from 2007 to 2021 for 19 developing and 19 developed countries. Our results show significant comovement patterns between ESG returns and stock returns at various frequencies, time scales, and sample episodes in all countries, particularly during periods of financial turmoil. For the most part, we document positive (in-phase) comovements between the stock returns and ESG returns in developing countries and negative (out-of-phase) comovements in developed countries. This implies limited portfolio gains from adding ESG stocks to portfolio diversification in developing countries but significant gains in developed countries.Copyright (c) 2022 Borsa Istanbul Anonim S, irketi. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Return and Risk Spillovers between ESG Global Index and Stock Markets: Evidence from Time and Frequency Analysis

In this paper, we examine the comovements between stock market returns and investments that take into account Environmental, Social, and Governance (ESG) factors by studying interconnections between the two returns in time and frequency space. We study interdependencies between the conventional stock market and ESG stocks using daily data from 2007 – 2021 for a set of 19 developing and 19 developed countries. Our results show significant comovement patterns between ESG returns and stock returns at various frequencies, time scales, and various sample episodes in all countries, particularly over financial turmoil episodes. For the most part, we document positive (in-phase) comovements between the stock returns and ESG returns in developing countries and negative (out-of-phase) comovements in developed countries. This implies limited portfolio gains from adding ESG stocks to portfolio diversification in developing countries but significant gains in developed countries

Connectedness and risk spillovers between crude oil and clean energy stock markets

This research investigates the relationship between clean energy stock and oil market returns utilizing Granger predictability in distribution and quantile impulse response analysis. We find that clean energy stock returns Granger predict oil price returns during "normal times" based on the distribution's center, but not vice versa. During bullish market episodes, there is bidirectional Granger predictability between the returns of clean energy stocks and oil market returns. Nonetheless, we find that clean energy stock returns Granger predict oil returns in bearish markets without any evidence of the contrary. This indicates that oil returns cannot be used to hedge the downside risk associated with renewable energy company purchases. Quantile impulse responses for the relationship between clean energy stocks and the crude oil market reveal bidirectional and significant responses, where a negative shock during an extremely down market reveals a negative response in the other market and a positive shock during an extremely up market reveals a significant positive response. This shows that neither market can be utilized to offset risks in the other market

Welfare cost of inflation in a stochastic balanced growth model

There is a large and growing literature on the welfare cost of inflation. However, work in this area tend to find moderate estimates of welfare gains. In this paper we reexamine welfare costs of inflation within a stochastic general equilibrium balanced growth model paying a particular attention to recursive utility, portfolio balance effects, and monetary volatility and monetary policy uncertainty. Our numerical analysis shows that a monetary policy that brings down inflation to the optimum level can have substantial welfare effects. Portfolio adjustment effects seem to be the dominant factor behind the welfare gains.Inflation Monetary policy Stochastic growth models

Volatility Spillovers and Contagion During the Asian Crisis: Evidence from Six Southeast Asian Stock Markets

Using a multivariate generalized autoregressive conditional heteroskedasticity (GARCH-M) model, we investigate volatility spillovers in six Southeast Asian stock markets around the time of the 1997 Asian crisis. We focus on interactions with the U.S. market as a world financial market, and with the Japanese market as a regional financial market. We also use bivariate GARCH-M models to examine the behavior of individual markets and their interactions with other markets in the region. All models lend support to the idea of the "Asian contagion," which started in Thailand and rapidly spread to other markets.Asian financial crisis, contagion, stock markets, time series models,