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"We investigate consumer"

"We investigate consumer price convergence for 82 Indonesian cities using monthly data from 2014 to 2019. To do so, we employ recent techniques of club convergence and weak sigma convergence. The results reveal, first, consumer price divergence, implying price rigidities across the cities. Second, we find four clubs, suggesting that Indonesian cities converge along four unique transition paths. Third, we find weak evidence of consumer price convergence, suggesting that prices among Indonesian cities adjust, but not freely. Policy should therefore consider unique convergence paths for each club to promote stronger consumer price convergence."

"ABSTRAKThis paper evaluates monetary policy transmission in both tranquil and turbulent periods for Mexico, Indonesia, Nigeria, and Turkey. Using a structural vector autoregressive model, we find that the effect of structural shocks from supply, demand, and financial sources tend to fizzle out faster for Nigeria and Mexico compared to Indonesia and Turkey. Another important finding is that while monetary authorities in Indonesia and Turkey are more responsive to inflation those in Mexico and Nigeria are more influenced by the exchange rate. We also observe differences in the conduct of monetary policy between the tranquil and turbulent periods."

"This paper evaluates monetary policy transmission in both tranquil and turbulent periods for Mexico, Indonesia, Nigeria, and Turkey. Using a structural vector autoregressive model, we find that the effect of structural shocks from supply, demand,and financial sources tend to fizzle out faster for Nigeria and Mexico compared toIndonesia and Turkey. Another important finding is that while monetary authorities in Indonesia and Turkey are more responsive to inflation those in Mexico and Nigeria are more influenced by the exchange rate. We also observe differences in the conduct of monetary policy between the tranquil and turbulent periods."

"ABSTRAKWe use a generalized autoregressive conditional heteroskedasticity dummy approach to analyze the influence of calendar anomalies on conditional daily returns and risk for the stock markets of Brazil, Russia, India, China, and South Africa from 1996 to 2018. Month-of-the-year, turn-of-the-month, day-of-the-week, and holiday effects are investigated. The most striking day-of-the-week effect is found for Tuesdays. The turn-of-the-month effect is validated, while, interestingly, we find no evidence of a January effect. A general holiday effect is not documented, but the Indian market shows a significant pre- and post-holiday effect, the Chinese market is anomalous before public holidays, and the South African market is affected only after holidays."

"Using the Consumer Price Index (CPI) data of 82 Indonesian cities, we propose the hypothesis of heterogeneity in the cities’ contribution to the aggregate Indonesian CPI. Using a price discovery model fitted to monthly data, we discover that (1) of the 23 cities in the province of Sumatera, five contribute 44% and nine contribute 66.7% to price changes, and (2) of the 26 cities in Java, four alone contribute 41.6% to price changes. Even in smaller provinces, such as Bali and Nusa Tenggara, one city alone dominates the change in aggregate CPI. From these results, we draw implications for maintaining price stability."

"ABSTRAKThe expected equity risk premium is a key input in various financial applications. Different methods exist for estimating the risk premium. This paper applies two approaches to estimate it in the markets of Greater China. More specifically, the historical average and relative estimation are carefully examined. The first approach is applied to estimate the equity risk premium when the markets are recovering from a trough. Then the relative estimation approach is applied to justify those findings, taking into consideration the lower rate of return required of Chinese investors due to a lack of investment opportunities. After these adjustments, the risk premium in Mainland China is found to be close to those in Hong Kong and Taiwan. All of these markets have a higher risk premium than in the US market. The risk premiums for the Shanghai and Shenzhen markets are about 8% and 10%, respectively. The risk premiums for the Hong Kong and Taiwan markets are 8% and 9% compared to a long-term forward-looking risk premium of about 4% for the US market."