Macroeconomic Shocks and Economic Performance in Malaysia: A Sectoral Analysis

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

 

2The paper explores the impact of COVID-19, the Russia-Ukraine War, inflation and contractionary U.S. monetary policy on Malaysian economy, which is relavant enough. However, there are additional points to improve the quality of the paper:

1)      In abstract, it could be better to emphasize the contribution of the research to related literature.

2)      It could be better to underscore the scientific value added/contributions of the paper in introduction, too. And question of “why this particular method is used” should be justified here (This should come from Literature discussion).

3)      In my opinion, the rows from 68 to 81 which is about the results and policy implications is unnecessary to be reflected in introduction.

4)      The measure of U.S. monetary policy surprises is denoted by Mon(t) in (1) equation. When reflecting the model results (row 179) B&S is used for this indicator. It could be better to use the same notation.

5)      Below the Figure 1 authors state “Forecasted stock prices are obtained from a regression of the sectoral stock returns on 1) the return on the Malaysian stock market, 2) the return on the world stock market, 3) news about Malaysian consumer price index inflation, 4) the change in the log of the ringgit/dollar exchange rate, and 5) the change in the log of the dollar spot price for Dubai crude oil.” However there is no information about main statistic characteristics of these models and their adequacy. For forecasting, models need to meet certain conditions.

6)    In conclusion, rows from 389 to 395 is approximately the repetition of the sentences in introduction. İt could be better to enhance findings, limitations, underscore the scientific value added of the paper, and/or the applicability of contributions/shortages and future study in this part.

 

 

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

This study aims to explore the relationship between stock returns across various sectors of the Malaysian economy and fluctuations in both domestic and global macroeconomic factors, including the domestic and world stock markets, US monetary surprises, inflation, and the US-Malaysian exchange rate. However, the paper does not effectively address its research question. To improve the paper and address the concerns raised, consider the following steps:

 

1.       Refine the Research Question: Clarify and expand the research question to ensure it aligns well with the objectives and scope of your study. You discuss about major global events but they are not included in the regression. It is a clear misalignment of the rationale of the paper and your study.  

2.       Methodology Adjustment: Reassess and adjust the methodology to better suit the research question. I have three specific suggestions:

a.       Explain each variable construction clearly and make sure that each variable measures shocks to align with the paper. Otherwise, remove “Shocks” from the title.

b.       It suffers from omitted variables bias. The sectoral returns are the reflection of the expected performance of the firms within the sector, but your regression has no variables that capture sector-specific firm characteristics. One possible approach would be to run return generation regression on Emerging Markets Factors. The data on the Emerging Markets Factors can be obtained from Fama and French data library: https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html. Use the errors from the first regression to regress on the macroeconomic variables.

c.       Instead of using the single equation multiple regression, consider multivariate time series regression models or SUR models and GLS estimation technique.

3.       Comprehensive Literature Review: Conduct a more thorough and focused literature review. Ensure that it directly supports your thesis and research question. This should include a critical analysis of previous studies, identifying gaps your research aims to fill and avoid unrelated literature. Instead of discussing one paper at a time, combine them based on the theme of the paper in the review.

4.       Discussion and Policy Implications: While discussing the results, stay within the scope of your research. If discussing policy implications, ensure they are directly related to your findings and are realistic given the scope of your study. In my view, the discussion goes beyond the scope of the paper.

5.       Clarity and Coherence: Throughout the paper, ensure that your arguments are clear, coherent, and logically structured. Each section of the paper should seamlessly connect to the next, maintaining a clear focus on the research question.

 

By addressing these areas, your paper will have a stronger foundation, clearer focus, and be better positioned to contribute meaningfully to the understanding of the Malaysian economy and its interaction with global economic variables.

Comments on the Quality of English Language

None

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

1)     What is the exact definition of “exposure” from Tab. 1? Which coefficient/parameter from the printed equations in the text does it represent?

2)     The applied model is not tested against any benchmark. First, it is well-known fact that often adding regressors improves forecast accuracy. Secondly, it seems that in fact the constructed model roughly measures linear correlation significance. For claiming some causality, impacts etc. a bit more reasoning would be required.

3)     The estimated model was not diagnosed and no robustness checks were done.

4)     From the initial parts of the paper is seems that Malaysia would be somehow analyzed in the context of shocks. This would require some particular periods to be defined, break point analysis, etc. which are missing. Just simple linear regression seems to be done in the paper.  

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

In conclusion, rows from 581 to 588 is better suited for introduction.

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

I appreciate the author's efforts in revising the paper and addressing the comments I previously made. The improvements in the writing and literature review are notable. However, I suggest further enhancing the literature review by organizing it thematically or based on the findings and theoretical underpinnings, rather than summarizing individual references separately. This approach would provide a more cohesive and insightful overview.

My major concern related to methodology has not been addressed adequately.

(a)    VAR is a standard model. No need to specify equations (1) to (3). One explicit equations involving variables of interest is sufficient in a standard matrix form is enough. The current specification should be improved with matrix notation. No results of VAR were reported. Appropriate application of VAR would include impulse response analysis and variance decomposition. Without proper model specifications and model diagnostics, we cannot conclude that an increase in oil price causes an increase in Malaysian stock returns. What is the theory behind such a conclusion? Did you control global liquidity during the COVID crisis? Did you do an additional causality test before reaching this conclusion? I cannot agree with the author’s conclusion without further documentation of the results.

(b)    Estimated results of equation (4) shows that majority of betas on the variables of interest are statistically insignificant. One regression and one significant coefficient is not sufficient to make a policy recommendation. The author should provide a robustness test for each significant variable before concluding. The omitted variable bias still persists. The alternative solution is to gather many domestic macroeconomic variables, derive principle components, and use them in the regression in addition to your variables of interest.

(c)     Figure 1 should be supplemented by some measures of forecast errors to gain further insight.

(d)    Results should be presented in more professional format. Macroeconomic variables are poor determinants of stock returns.  There should be alternative tests before making recommendations.

I hope these comments help.

 

Thanks

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors

1)     What does it mean “beta to” in Table 1?

2)     All abbreviations of variables should be defined.

3)     What is the data frequency? How many observations were used? It might happen that the ratio of observations to estimated parameters in an equation is too small to make meaningful regression analysis.

4)     Still there is no benchmark model like ARIMA or no change. Maybe model with no variables would make better or at least the same accurate forecast as your, meaning that adding these variables you used was really not giving any important information at all.

 

Author Response

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Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

I would suggest going back to revisit all the comments I made in the second round and address them point by point. 

Comments on the Quality of English Language

My comments are not addressed properly. However, it is much improved. I would suggest going back to revisit all the comments I made in the second round and address them point by point.

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors

My comments were implemented. Anyways, beside reporting and comparing forecast accuracy measure (MSE) also some test like Diebold-Mariano should be applied to strengthen conclusions.

Author Response

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