Synchronization of business cycles and economic policy linkages in ASEAN

Sethapramote, Yuthana

doi:10.1016/j.asieco.2015.06.003

Cited by 19 publications

(14 citation statements)

References 18 publications

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“…In 2015, ASEAN countries expanded their economic collaboration to the ASEAN+6, a grouping of 16 countries comprising the 10 ASEAN member countries are Brunei, Burma, Cambodia, Indonesia, Philippines, Malaysia, Laos, Singapore, Thailand and Vietnam, and six other countries in the Asia-Pacific region: Australia, China, India, Japan, Korea and New Zealand. Sethapramote (2015) shows a strong co-movement pattern which is the key success factor of economic development. The results of the study present that Thailand, Malaysia, Singapore, and the Philippines generally exhibit higher degrees of correlation than other ASEAN countries.…”

Section: Introductionmentioning

confidence: 99%

Factors Influencing Retail Investors’ Trading Behaviour in the Thai Stock Market

Paisarn¹,

Chancharat²,

Chancharat³

2021

AABFJ

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This paper investigates trading behaviour among Thai retail investors in 2016. Using detailed survey data from 491 investors, we examine the characteristics and behavioural patterns that lead to investor bias. Empirical results in the behavioural finance literature indicate that retail investors may not behave reasonably. Behavioural biases may influence investor decisions and affect financial markets. These studies, however, are limited to subsamples of the overall investor groups studied and mainly focus on developed markets. We find that biases are common among investors and that men are more overconfident than women. Moreover, we discover that investors with more experience in trading are less likely to hold their stocks for long periods of time. Further, investors aged 45 and younger hold more diversified portfolios. Another finding is that participants with an income of more than 50,000 Baht a month and/or who employ a number of brokers hold more diversified portfolios. This evidence is consistent with the findings that have been reported for Turkey, India, and Vietnam, indicating that demographic factors are useful for distinguishing between investors in terms of the level of overconfidence bias they exhibit. This result confirms that demographic factors play a role in differentiating and classifying retail investors and should motivate future researchers to consider these factors in their research.

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Section: Introductionmentioning

confidence: 99%

Factors Influencing Retail Investors’ Trading Behaviour in the Thai Stock Market

Paisarn¹,

Chancharat²,

Chancharat³

2021

AABFJ

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“…This issue is investigated also in other countries: China (Herrmann-Pillath et al 2014), Germany (Zuiddam 2016), Ukraine (Yaskal 2013) and ASEAN-members (Sethapramote 2015).…”

Section: Economic Integrationmentioning

confidence: 99%

Spatial Distribution of Economic Activities and Internal Economic Integration in Romania

Yaskal¹,

Maha²,

Petrashchak³

2020

JURA

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This paper aims to consider two tendencies in economy simultaneously: internal integration within the country and localization of economic activities. Firstly, we examine the quantitative measurement of internal economic integration in Romania. Different methods of economic integration measuring have been developed over time, so we have defined and discussed three approaches. To estimate a level of internal integration the link between the region's share in the total output and production factors was estimated and the pattern of distribution of these shares among the regions of Romania was assessed. The calculations have underlined an increasing tendency to deepen the internal economic integration of the Romanian economy. Secondly, the analysis of spatial distribution of economic activity has demonstrated that the capital region Bucharest-Ilfov concentrates the biggest share of employment and production. This indicates that initially there were higher economic activities and a labor deficit has been created, which was later covered by moving employees from other regions. As a result, the capital region concentrates 14.35% of the civil economically active population and 26.78% of the regional gross domestic product in 2014. By computing the location coefficient, we have observed that the counties with the biggest shares in the total GDP are characterized by a higher level of specialization simultaneously in many sectors.

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“…Since trade and financial integration between countries increase, the countries have the synchronization of the business cycle (Kose et al, 2003). Sethapramote (2015) studies the business cycle synchronization of the Association of Southeast Asian Nations (ASEAN) from the internal and external regions. His study points out that trade transmission is an important factor in ASEAN synchronization because they rely on export revenue.…”

Section: Literaturementioning

confidence: 99%

Forecasting Economic Cycle With a Structural Equation Model: Evidence From Thailand

Pumjaroen

Vichitthamaros

Sethapramote

2020

IJEFI

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The study proposes a partial least squares structural equation modeling (PLS-SEM) evaluating the relationship among composite leading indices (CLIs) to forecast the economic cycle (EC) instead of using only individual CLI. The model of quarterly data in Thailand during 2013-2018 includes five constructs representing economic sectors that have the potential to be CLIs of EC. Those are two short-term CLIs including Short-leading economic index (SLEI) and International transmission (Trade channel) (ITT). SLEI composes Narrow money, Business sentiment index (Next 3 months), and Export volume index while ITT constructs from CLI of the major export partners. The Financial cycle (FC) has the potential to be the medium-term CLI, which includes Housing price index, Household debt to GDP, and Household debt. While Monetary condition (MC) and International transmission (Monetary channel) (ITM) are the long-term CLI. MC consists of Policy interest rate and real effective exchange rate whereas ITM is represented by the global economy using CLI for OECD and non-member economies as a proxy. The evidence from the forecasting performance in the out-of-sample by PLS-SEM outperforms the alternative models for all short-term, middle-term, and long-term periods. Therefore, the study convinces to apply the PLS-SEM to forecast EC.

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Synchronization of business cycles and economic policy linkages in ASEAN

Cited by 19 publications

References 18 publications

Factors Influencing Retail Investors’ Trading Behaviour in the Thai Stock Market

Factors Influencing Retail Investors’ Trading Behaviour in the Thai Stock Market

Spatial Distribution of Economic Activities and Internal Economic Integration in Romania

Forecasting Economic Cycle With a Structural Equation Model: Evidence From Thailand

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