Assessing competitiveness of ASEAN-10 economies

Tan, Khee Giap; Tan, Kong Yam

doi:10.1504/ijebr.2014.065509

Cited by 5 publications

(9 citation statements)

References 2 publications

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“…Lall (1992) argues that at the country level, capabilities can be grouped under three broad headings: physical investment, human capital and technological effort. Tan and Tan (2014) also agree with Lall (1992) that education, physical infrastructure and technological infrastructure are important elements for national technological competitiveness (NTC). Physical investment refers to plant and equipment that are needed for industries to exist.…”

Section: Manufacturing Composite Index Framework and Their Shortcomingsmentioning

confidence: 64%

“…The conceptual model of the MCI presented in this work is adapted from Delgado-Márquez and García-Velasco (2018), Fischer et al (2018), Terzi c (2017), Ezell andAtkinson (2011), Lall (1992), Abramovitz (1986), Faberberg (1994), Archibugi and Coco (2004), Tan and Tan (2014), Milenkovic et al (2016), Shaker and Zubalsky (2015) and Lall and Albaladejo (2003). Lall (1992) argues that at the country level, capabilities can be grouped under three broad headings: physical investment, human capital and technological effort.…”

Section: Manufacturing Composite Index Framework and Their Shortcomingsmentioning

confidence: 99%

“…The NTC uses data from the World Bank but does not include data on importation of manufacturing technologies. In this work, technological infrastructure and physical infrastructure are important elements to be considered in the conceptual development of the MCI as used in the Asia Competitiveness Institute Index (Tan and Tan, 2014) Abramovitz (1986) and Faberberg (1994) indicate that there are three essential ingredients explaining differences in the rate of technological changes across countries.…”

Section: Manufacturing Composite Index Framework and Their Shortcomingsmentioning

confidence: 99%

“…Computation of MCI, complemented with clustering algorithm (such as Wards and Fuzzy c-mean) have been used to cluster countries (Shami et al, 2013;Shaker and Zubalsky, 2015). "What If" simulation has also been used to make recommendations on structural reforms in the policy of the country (Tan and Tan, 2014).…”

Section: Cr 302mentioning

confidence: 99%

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Repositioning a country for global manufacturing competitiveness: a case of South Africa

Gates

Adetunji

2020

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Purpose This study aims to develop an artifact to measure the level of manufacturing competitiveness of a country in the global context and provide a suitable interpretation mechanism for the measured values, and to provide prescriptive solution where necessary so that the country can develop an actionable plan of program to move from the current level of global competitiveness to another such that they could provide more economic opportunities for their citizenry. Design/methodology/approach A manufacturing competitive index (MCI) was developed which includes relevant variables to capture a country’s manufacturing activity level in an economy with a balanced perspective. Reliable international sources were used. Ward algorithm was used to identify clear clusters of performance upon which competitive gaps were measured and improvement projects were identified and prioritized to obtain the best value for cluster transitional plan. Findings This study shows that the case country is not doing as well as it wants to believe, even when the relevant technology import measures were included in the expanded metric, but also, the next level of competitiveness is achievable within the national budget if proper prioritization is done. Originality/value The paper presents a cocktail of indexes that is more exhaustive of MCI, including both research capacity and technology import variables. It also uses clustering mechanism to provide a proper context to interpret the MCI scores in the context of peer nations. It presents a gap determination methodology and shows how priority projects could be logically selected to close measured gaps based on anticipated value from budget expenses

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Section: Manufacturing Composite Index Framework and Their Shortcomingsmentioning

confidence: 64%

Section: Manufacturing Composite Index Framework and Their Shortcomingsmentioning

confidence: 99%

Section: Manufacturing Composite Index Framework and Their Shortcomingsmentioning

confidence: 99%

Section: Cr 302mentioning

confidence: 99%

See 2 more Smart Citations

Repositioning a country for global manufacturing competitiveness: a case of South Africa

Gates

Adetunji

2020

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“…Hence, this theory suggests a positive relationship between monetary policy and banking profitability. Further interrogation into the monetary policy literature suggests that monetary policy can be classified as either being expansionary or contractionary (Altavilla et al , 2018; Tan et al. , 2010; Kishan and Opiela, 2006).…”

Section: Literature Reviewmentioning

confidence: 99%

Monetary policy decisions and bank profitability: evidence from an emerging economy

Dzeha

Boachie

Kriese

et al. 2022

IJOEM

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PurposeThis study provides empirical evidence for the first time on how different measures of monetary policy affect banking profitability in Ghana.Design/methodology/approachProviding empirical evidence on how different measures of monetary policy affect banking profitability in Ghana using 29 banks for period between 2006 and 2016, new monetary indexes are developed and a robust panel random effect models is employed with year effect controls.FindingsThe results show that while increase in monetary policy basis point reduced banking profitability, average monetary policy rate stimulated banking profitability. Interestingly, the monetary policy basis point and rate indexes developed reduced and enhanced banking profitability, respectively. While these results may sound contradictory, they have both theoretical and empirical backing. Thus, basis point increments serve a monetary policy tightening condition which leads to higher loan prices, lower borrowing and declined profitability in the short run. However, in the long run, banks adjusted their loan prices and deposits to reflect basis point changes in their favor, hence the positive effect of average monetary policy rate on banking profitability. Additionally, monetary policy easing which represents decline in monetary policy basis point and rate enhances banking profitability.Practical implicationsThese findings imply bank managers may take advantage of monetary policy easing to maximize profits in the banking sector of Ghana. Also, the monetary policy committee must be mindful of monetary policy tightening through basis point change since upward basis point increments reduce banking profitability.Originality/valueThis study provides empirical evidence for the first time on how different measures of monetary policy (developing indexes from monetary policy basis point and monetary policy rate) affect banking profitability in an emerging economy as Ghana.

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Measuring the Indonesian provinces competitiveness by using PCA technique

Runita

Fajriyah

2017

J. Phys.: Conf. Ser.

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Assessing competitiveness of ASEAN-10 economies

Cited by 5 publications

References 2 publications

Repositioning a country for global manufacturing competitiveness: a case of South Africa

Repositioning a country for global manufacturing competitiveness: a case of South Africa

Monetary policy decisions and bank profitability: evidence from an emerging economy

Measuring the Indonesian provinces competitiveness by using PCA technique

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