Relief Policy and the Sustainability of COVID-19 Pandemic: Empirical Evidence from the Italian Manufacturing Industry

Round 1

Reviewer 1 Report

Dear Authors,

I'm glad I got a chance to revise your manuscript. The work is interesting but needs to be more in-depth. It presents some critical issues.

First of all, the theoretical background is not clarified at all. The literature on the consequences of unexpected business shocks is broad and authoritative. I suggest the authors go into this before elaborating on the analysis model, which has some weaknesses.

Furthermore, the Explanatory variable is Labor cost (per employee). That is wrong. This variable does not seem to be a good choice since the measures taken by the government prevented redundancies. That proxy can be used outside economic systems that benefit from system protection measures. In addition, the reduction in labour costs in 2020 did not depend on redundancies, which the legislation prevented from being carried out, but on other factors: the social shock absorbers that helped companies to overcome downtime and reduce labour costs; the permanent closure of certain commercial activities. The results are misleading because the study does not distinguish the two aspects.

Another critical aspect is the choice of the sample analysed. Not all sectors have been affected by downtime, and for some, there has been a significant increase in turnover (for example, pharmaceuticals, consumer goods, etc.). These sectors had to be targeted and excluded from the sample.  

Finally, I do not see a particular contribution of the study to the existing literature. Aida Burovandik's database generates all data used, and regression is caused by ad hoc software. However, the results are incorrect because the sample has not been correctly identified. 

Good luck with your work.

Author Response

Reviewer 1

Comment 1

I'm glad I got a chance to revise your manuscript. The work is interesting but needs to be more in-depth. It presents some critical issues.

Answer 1

Thank you very much for the positive comment. The new version has been improved according to the comments and suggestions, and we believe that both the readability and the robustness of the work have benefited from them.

Comment 2

First of all, the theoretical background is not clarified at all. The literature on the consequences of unexpected business shocks is broad and authoritative. I suggest the authors go into this before elaborating on the analysis model, which has some weaknesses.

Answer 2

Authors have introduced a new section (Section 2 – Literature review and hypotheses), specifying the current background, relative gaps in literature, and justifying our contribution: “…Storm (2021) highlights that Italian interventions has been negatively affected by the fiscal capacity of government to raise spending to cushion the economic impact of the health emergency for vulnerable businesses. Indeed, according to the author, even if the COVID-19 mortality was relatively high, the per-capita spending was relatively low because the high public debt and governments’ limited access to external financial resources. As a consequence, the pandemic had a significant economic negative impact on the national economy. According to Cetrulo (2021), the Italian GDP contracted by about 6.6% between 2019 and 2020, while the reduction in working hours was about 7.5%. Moreover, the author denotes that, compared to 2019, employment declined by 414,000 units (-1.8%), a drop that is mainly concentrated among fixed-term employees (-383,000) and self-employed workers (-129,000). Indeed, the Italian government’s interventions to support economic activities were mainly oriented toward protecting permanent employees, preventing the dismissing of their workers and reducing the cost of unproductive human resources through the introduction of layoff (Gallo and Raitano, 2022). Besides these measures, which significantly reduced the potential uneven impact of the pandemic, preserving job stability for millions of workers (Carta and De Philippis, 2021), there were no interventions to support the demand for final goods and spending by consumers, as well as no significant efforts to support the adoption of new digital services by firms and/or the introduction of innovative products on the market. Moreover, there were limited interventions to support workers’ resilience, facilitating opportunities for smart-working (Tokarchuk et al., 2021)…”.

Cited literature:

Carta, F., & De Philippis, M. (2021). The impact of the COVID-19 shock on labour income inequality: Evidence from Italy. Bank of Italy Occasional Paper, nr. 606.

Cetrulo, A. (2021). Is remote working here to stay? Lessons and ideas for a post-pandemic future. Rivista quadrimestrale dell’INAPP, Anno XI, Vol. 2(2021), 36-49

Gallo, G., & Raitano, M. (2022). SOS incomes: simulated effects of COVID-19 and emergency benefits on individual and household income distribution in Italy. Journal of European Social Policy, forthcoming.

Storm, S. (2021). Lessons for the Age of Consequences: COVID-19 and the Macroeconomy. Review of Political Economy, 1-40.

Tokarchuk, O., Gabriele, R., & Neglia, G. (2021). Teleworking during the COVID-19 crisis in Italy: Evidence and tentative interpretations. Sustainability, 13(4), 2147.

Comment 3

Furthermore, the Explanatory variable is Labor cost (per employee). That is wrong. This variable does not seem to be a good choice since the measures taken by the government prevented redundancies. That proxy can be used outside economic systems that benefit from system protection measures. In addition, the reduction in labour costs in 2020 did not depend on redundancies, which the legislation prevented from being carried out, but on other factors: the social shock absorbers that helped companies to overcome downtime and reduce labour costs; the permanent closure of certain commercial activities. The results are misleading because the study does not distinguish the two aspects.

Answer 3

We agree with the limits of our investigation, which relies on the available data. We have highlighted this point in the manuscript: “…Note that, even if there are no available data about the amount of layoffs requested by each firm, we can stratify the intensity of this measure by observing the labor cost per employee. Indeed, firms with authorized layoff were able to decrease this key cost in 2020 and, investigating the variation in the labor cost between 2019 and 2020, we can estimate the impact of such relief policy. Indeed, firms were not allowed to fire their employee in 2020, which means that a reduction in this cost can be explained with the access to layoff by firms. Accordingly, the observations in 2019 represent the counterfactual against which the impact of this relief policy is assessed…”. Moreover, in the conclusions, we have specified the limits of our work: “…Although the results presented here are interesting, our work has clear limits since we focus on a very peculiar case study, i.e., the Italian manufacturing industry, and we have no access to micro data that could corroborate our expectations (e.g., the ability of different occupations to work from home, and access to layoff). If new and more recent data will be available, our future studies will investigate further these dynamics to corroborate the findings gathered thus far. In addition, if data on other manufacturing industries become available, there will be opportunities to investigate alternative policy reliefs, and to compare different approaches to mitigate next waves…”.

Comment 4

Another critical aspect is the choice of the sample analysed. Not all sectors have been affected by downtime, and for some, there has been a significant increase in turnover (for example, pharmaceuticals, consumer goods, etc.). These sectors had to be targeted and excluded from the sample.

Answer 4

Thank you very much for this comment, which gives us the possibility to clarify our model and the key role of industrial sectors. Accordingly, we have improved the manuscript, explaining that “…we introduce fixed effects in our model: NACE code – 2 digit (FE), which is a dummy variable equal to 1 according to 2 digits (24 classes), 0 otherwise; and geographical Macro area, which is a dummy variable equal to 1 according to NUTS1 (5 classes), 0 otherwise. NACE codes are essential to control the strategic businesses (e.g., food supply chain) that were allowed to continue operating during the national lockdown…”. Table A.3 in the Appendix (Table A.3 – Fixed effects adopted in the RE regression model: NACE codes - 2 digits) reports all the coefficients.  

Comment 5

Finally, I do not see a particular contribution of the study to the existing literature. Aida Burovandik's database generates all data used, and regression is caused by ad hoc software. However, the results are incorrect because the sample has not been correctly identified. 

Answer 5

Authors do not agree with the comment. On the one hand, as well as highlighted in the manuscript “…To the best of our knowledge, no investigations have been carried out into the impact of COVID-19 on Italian manufacturing industry, which represents an opportunity to provide new and practical insights to managers and policy makers…”. On the other hand, we are considering industrial sectors (NACE codes - 2 digit) as control variables and, for this reason, we believe the sample has been correctly identified. See Table A.3 in the Appendix (Table A.3 – Fixed effects adopted in the RE regression model: NACE codes - 2 digits).  

Comment 6

Good luck with your work.

Answer 6

Regardless of your final judgment, the authors would like to thank you for your very useful comments, which have helped us to improve the manuscript.

Author Response File: Author Response.docx

Reviewer 2 Report

I have uploaded a file with detail comments.  

Comments for author File: Comments.pdf

Author Response

Reviewer 2

Comment 1

Topic: The topic of the manuscript is appropriate and covers all the important aspects of the research.

Answer 1

Thank you very much for the positive comment. The new version has been improved according to the comments and suggestions, and we believe that both the readability and the robustness of the work have benefited from them.

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Comment 2

Abstract: Abstract is well written but still can be improved by incorporating the following suggestions:

• After defining the purpose, authors should provide the importance of the research.
• Then provide detail of the methodology (population, sampling, scales, tests, etc.).
• Give detail of results
• And in the end provide implications (two-three implications)

Answer 2

According to the comment and the suggested structure, we have re-drafted the abstract as following: “…This work investigates the impact of COVID-19 on the Italian manufacturing industry, testing whether the recovery measures introduced by the government were effective in alleviating the economic consequences of the virus in 2020. In particular, this work aims to address the following key issues: impact of COVID-19 on the Italian manufacturing industry (1); evaluation of the adopted recovery measures (2). Considering the current situation, with the war in Ukraine and the related gas crisis across European Union, such investigation on policy relief is even more relevant, contributing on the current debate. Adopting RE models and considering the latest economic and financial information available, authors analyze active private limited firms in the Italian manufacturing industry between 2019 and 2020, investigating the impact of layoff on their productivity (i.e., Total Factor Productivity) and profitability (i.e., Return On Assets), as well as their expected probability of default. According to the results of these regression models, and assuming 8 weeks of layoff, we can observe an increase in productivity (between 1.20% and 1.59%), a decrease in profitability (1.47%) and an increase in bankruptcy risk (2.27%). Hence, the relief policy was not able to alleviate the economic consequences of COVID-19 for these firms, even though the layoff were able to support their productivity. Practical implications concern the necessary improvements for the above relief policy, i.e., interventions to support the demand of manufactured products (I), interventions to support the digitalization of services (II), interventions to support the remote working (III), and finally interventions to support the introduction of innovative products on the market (IV)…”.

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Comment 3

Keywords: Add more keywords from your variables (Labor cost (per employee), TFP (Revenues), TFP (Added value), ROA, and Probability of default)

Answer 3

Authors agree with the reviewer, and the manuscript has been improved accordingly. In details, we have added “Total Factor Productivity (TFP)”, “Return On Assets (ROA)”, “labor cost”, “probability of default”.

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Comment 4

Introduction: The current introduction is weak and needs a lot of improvement. Some changes are recommended as under:

• Introduction should provide a detailed background of the study. Currently, a brief background is provided.
• No detail of the research gap is provided which is an important aspect of the introduction section.
• How will the current study address the gap identified? No detail is given.
• What is the structure of the current paper? No detail is given in the introduction section.

Answer 4

Authors agree with the comment, even if this is a Brief Report, and the introduction has been improved accordingly. In particular, focusing on the methodology, we have specified that “…We test the proposed hypothesis by analyzing active private limited firms in the Italian manufacturing industry between 2019 and 2020 and by combining information extracted from their balance sheet and economic statements, so that we can investigate the relation between firms’ access to layoff and their productivity, profitability and default probability…”, and then, considering the research gap, we have highlighted that “…To the best of our knowledge, no investigations have been carried out into the impact of COVID-19 on Italian manufacturing industry, which represents an opportunity to provide new and practical insights to managers and policy makers…”. Afterwards, considering the structure, authors have improved the manuscript as following: “…The article is organized as following. Section 2 presents an overview of current literature and proposes the hypothesis. Section 3 introduces data and methodology, while Section 4 shows the collected results. Finally, Section 5 proposes some conclusions, focusing on the main practical implications…”.

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Comment 5

Material and Method:

• Explain Table 2 in detail.

Answer 5

According to the suggestion, we have specified that “...every row represents an industrial sector of the Italian manufacturing industry and it highlights the variation between 2019 and 2020 of TFP, ROA and probability of default, as well as the variation of the labor cost…”.

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Comment 6

Results: This section is well written and presented. Some suggestions for improvement are given below:

• Discuss results in detail.
• Add literature support with your all results.
• Theoretical and practical implications should be given separately.

Answer 6

Authors have improved the results section, proposing a sub-section for the discussion of the collected results and the main hypothesis (4.1 Discussion: relief policy and firm dynamics) and a successive sub-section with practical implications according to the collected results (4.2 Practical implications). Finally, we conclude the fourth section with a sub-section that discus the control variables and the collected evidence (Discussion: Firms characteristics and the institutional environment).

Considering the discussion of the results with respect other works, the manuscript has been improved as following: “…Considering current literature, these results are also coherent with some preliminary evidence proposed in the literature and based on the available information collected during the pandemic (e.g., Carletti et al., 2020). Even if the recent COVID-19 crisis has generated a concern that productivity (which was already at historically low levels) may further decline (Furceri et al., 2021), the Italian policy reform was able to maintain high level of productivity, decreasing the labor cost. Nevertheless, on the other hand, the relief policy was not able to support the businesses, with a significant decrease of their profitability and an increase of their default probability. Indeed, according to Del Rio-Chanona et al. (2020), there were demand-side changes due to peoples’ immediate response to the pandemic (e.g., reduced demand for goods or services). Moreover, sectors relating to manufacturing are more likely to be constrained by supply shocks with reductions due to the closure of non-essential industries and workers not being able to perform their activities at home. Our evidence can support these claims, as highlighted by the collected results. Taking these considerations into account, the successive sub-section proposes some practical implications…”.

Afterwards, considering the practical implications, the manuscript has been improved as following: “…Practical implications concern the necessary improvements for the above relief policy. In particular, according to results, the introduction of layoff could be integrated with interventions to support the demand of manufactured products. This measure could support the manufacturing industry in this difficult moment, raising their profitability and, in this way, decreasing their default probability. This is an essential measure, as well as highlighted by stakeholders (e.g., CONSOB).[1] Additional interventions could concern the digitalization of services to support the resilience of firms on the market, as well as interventions to support the introduction of innovative products that might respond to new necessity. In both cases, there could be opportunities to make these businesses more competitive on the market, especially in this critical context. Finally, even if the layoff adopted by the Italian government reduced the potential uneven impact of the pandemic, preserving job stability for millions of (fixed) workers, interventions to support the remote working could be advisable, fostering workers’ resilience (e.g., smart-work). Indeed, the possibility of working remotely regards a minority, and it is not equally distributed among the workforce (Cetrulo, 2021). Obviously, the workers excluded by this opportunity could face higher risk of negative outcomes (i.e., lower income or unemployment, as well as worst health conditions), and the pandemic had significantly worsened their conditions. Accordingly, the policy maker should adopt interventions to remove all technical, organizational and social features that might prevent this opportunity...”.

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Comment 7

One of the most important aspects of any scientific research process or research paper is a literature review that introduces the variables and provides detail of existing literature on all the variables of research. This essential part of the research paper is missing. Authors should add brief but comprehensive literature on the variables of current research including Labor cost (per employee), TFP (Revenues), TFP (Added value), ROA, and Probability of default. Also, discuss the relationship of these variables to any other reported crises around the world.

Answer 7:

We agree with the comment, and we have improved the manuscript supporting the adoption of our dependent variables (TFP, ROA, and Probability of default) and key explanatory variable (Labor cost) with recent and relevant literature: "... According to literature, TFP can be considered an evaluable indicator for measuring recession after crises, and many recent studies focus on the analysis of COVID-19, comparing pre- and post- pandemic (e.g., Furceri et al., 2021; Di Mauro and Syverson, 2020). In particular, considering data availability and coherently with Bosio et al. (2020) and Svarstad and Kostøl (2020), we propose two TFP indexes: revenue-based TFP and added value-based TFP, calculated as suggested by Petrin et al. (2004). Obviously, these indicators represent a different meaning of productivity: the former analyzes the sales growth over time, the latter considers the ability to generate profits from the operating activities of firms. Afterwards, according to literature (Abbassi et al., 2022; Kumar and Zbib, 2022), we propose a representative index for firms’ profitability, which is expressed in terms of Return on Assets (i.e., ROA) and it represents their ability in reacting to pandemic and/or other negative shocks (e.g., recession, war), considering the volatility of profits on total assets. Finally, according to Switzer et al. (2018) and Yin et al. (2022), the probability of default represents the financial health of firms, and a good proxy to estimate the impact of COVID-19, evaluating whether these businesses are not able to react rapidly to the unexpected conditions created by the pandemic. Focusing on the explanatory variable, coherently with current literature (e.g., Fang et al., 2022; Costa et al., 2022; Kassem, 2022), we have considered labor cost as a proxy of layoff, studying whether this measure contributed to reduce the negative impact of pandemic on firms’ performance…”.

Cited literature:

Abbassi, W., Kumari, V., & Pandey, D. K. (2022). What makes firms vulnerable to the Russia–Ukraine crisis?. The Journal of Risk Finance, forthcoming.

Bosio, E., Djankov, S., Jolevski, F., & Ramalho, R. (2020). Survival of firms during economic crisis. World bank policy research working paper, (9239).

Costa, S., De Santis, S., & Monducci, R. (2022). Reacting to the COVID-19 crisis: state, strategies and perspectives of Italian firms. Rivista di statistica ufficiale, nr. 1/2022.

Di Mauro, F., & Syverson, C. (2020). The COVID crisis and productivity growth. VOX CEPR Policy Portal, 16.

Fang, J., Gozgor, G., & Nolt, J. H. (2022). Globalisation, economic uncertainty and labour market regulations: Implications for the COVID‐19 crisis. The World Economy, 45(7), 2165-2187.

Furceri, D., Celik, S. K., Jalles, J. T., & Koloskova, K. (2021). Recessions and total factor productivity: Evidence from sectoral data. Economic modelling, 94, 130-138.

Kassem, S. (2022). Labour realities at Amazon and COVID-19: obstacles and collective possibilities for its warehouse workers and MTurk workers. Global Political Economy, 1(1), 59-79.

Kumar, S., & Zbib, L. (2022). Firm performance during the Covid-19 crisis: Does managerial ability matter?. Finance Research Letters, 102720.

Petrin, A., Poi, B. P., & Levinsohn, J. (2004). Production function estimation in Stata using inputs to control for unobservables. The Stata Journal, 4(2), 113-123.

Svarstad, E., & Kostøl, F. B. (2022). Unions, collective agreements and productivity: A firm‐level analysis using Norwegian matched employer–employee panel data. British Journal of Industrial Relations, forthcoming.

Switzer, L. N., Tu, Q., & Wang, J. (2018). Corporate governance and default risk in financial firms over the post-financial crisis period: International evidence. Journal of International Financial Markets, Institutions and Money, 52, 196-210.

Yin, J., Han, B., & Wong, H. Y. (2022). COVID-19 and credit risk: A long memory perspective. Insurance: Mathematics and Economics, 104, 15-34.

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Comment 8

Add implications in the discussion section as it is the most important section of the paper. Without implications, the paper has no use.

Answer 8

Authors completely agree with the suggestion. Hence, we have improved the discussion of results, highlighting practical implications: “…Practical implications concern the necessary improvements for the above relief policy. In particular, according to results, the introduction of layoff could be integrated with interventions to support the demand of manufactured products. This measure could support the manufacturing industry in this difficult moment, raising their profitability and, in this way, decreasing their default probability. This is an essential measure, as well as highlighted by stakeholders (e.g., CONSOB).[2] Additional interventions could concern the digitalization of services to support the resilience of firms on the market, as well as interventions to support the introduction of innovative products that might respond to new necessity. In both cases, there could be opportunities to make these businesses more competitive on the market, especially in this critical context. Finally, even if the layoff adopted by the Italian government reduced the potential uneven impact of the pandemic, preserving job stability for millions of (fixed) workers, interventions to support the remote working could be advisable, fostering workers’ resilience (e.g., smart-work). Indeed, the possibility of working remotely regards a minority, and it is not equally distributed among the workforce (Cetrulo, 2021). Obviously, the workers excluded by this opportunity could face higher risk of negative outcomes (i.e., lower income or unemployment, as well as worst health conditions), and the pandemic had significantly worsened their conditions. Accordingly, the policy maker should adopt interventions to remove all technical, organizational and social features that might prevent this opportunity...”.

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Comment 9

The paper is currently in abstract form and needs a lot of explanation and justifications.

Answer 9

Authors have introduced a new section (Section 2 – Literature review and hypotheses), specifying the current background, relative gap in literature, and justifying our contribution: “…Storm (2021) highlights that Italian interventions has been negatively affected by the fiscal capacity of government to raise spending to cushion the economic impact of the health emergency for vulnerable businesses. Indeed, according to the author, even if the COVID-19 mortality was relatively high, the per-capita spending was relatively low because the high public debt and governments’ limited access to external financial resources. As a consequence, the pandemic had a significant economic negative impact on the national economy. According to Cetrulo (2021), the Italian GDP contracted by about 6.6% between 2019 and 2020, while the reduction in working hours was about 7.5%. Moreover, the author denotes that, compared to 2019, employment declined by 414,000 units (-1.8%), a drop that is mainly concentrated among fixed-term employees (-383,000) and self-employed workers (-129,000). Indeed, the Italian government’s interventions to support economic activities were mainly oriented toward protecting permanent employees, preventing the dismissing of their workers and reducing the cost of unproductive human resources through the introduction of layoff (Gallo and Raitano, 2022). Besides these measures, which significantly reduced the potential uneven impact of the pandemic, preserving job stability for millions of workers (Carta and De Philippis, 2021), there were no interventions to support the demand for final goods and spending by consumers, as well as no significant efforts to support the adoption of new digital services by firms and/or the introduction of innovative products on the market. Moreover, there were limited interventions to support workers’ resilience, facilitating opportunities for smart-working (Tokarchuk et al., 2021). On the one hand, we expect the adoption of layoff supported the productivity of these firms, decreasing the labor costs while, on the other hand, we expect that their profitability decreased and default probability increased. Hence, following this reasoning, we seek empirical confirmation of a positive relation between access to layoff and productivity but, at the same time, we expect to observe a negative impact on profitability and default probability. More precisely, we expect:

H₁          higher productivity;

H₂          lower profitability;

H₂          higher default probability.

These are exactly the hypotheses that we test in our empirical investigation, expecting to confirm the limits of Italian policy relief during the pandemic. To the best of our knowledge, no investigations have been carried out into the impact of COVID-19 on Italian manufacturing industry, which represents an opportunity to provide new and practical insights to managers and policy makers…”.

______________________________

Comment 10

Overall, the paper is based on a novel idea and has the potential to be published. However, some minor changes, as recommended above, should be incorporated before acceptance.

Answer 10

Regardless of your final judgment, the authors would like to thank you for your very useful comments, which have helped us to improve the manuscript.

[1] See Commissione Nazionale per le Società e la Borsa (CONSOB). Link: https://www.consob.it/web/investor-education/crisi-sanitaria-economica

[2] See Commissione Nazionale per le Società e la Borsa (CONSOB). Link: https://www.consob.it/web/investor-education/crisi-sanitaria-economica

Author Response File: Author Response.docx

Reviewer 3 Report

The article is interesting, and the researched problem has scientific potential, but the paper has various deficiencies. Some problems need to be solved:

1. The paper does not describe a clear research plan with steps to be followed.

2. The literature review must be enriched particularly with recent sources (2019-2022).

3. I have not seen clear defined hypotheses or research questions.

4. The research method is descriptive. The paper would gain value if complex statistical methods were used to establish the relationships between variables (SEM, MANOVA, etc).

5. Also, a separate discussion section is necessary to show the results of the work in line with the results of other research.

6. In my opinion, a section of conclusions that includes theoretical and managerial implications, research limitations, and future research directions would be helpful. The current form of the conclusions briefly repeats what was stated in the results and discussion sections.

The article presents some scientific value and can be published after carefully reviewing the reported issues.

Author Response

Reviewer 3

Comment 1

The article is interesting, and the researched problem has scientific potential, but the paper has various deficiencies. Some problems need to be solved.

Answer 1

Thank you very much for the positive comment. The new version has been improved according to the comments and suggestions, and we believe that both the readability and the robustness of the work have benefited from them.

___________________________________

Comment 2

The paper does not describe a clear research plan with steps to be followed.

Answer 2

We have improved the Introduction, highlighting the steps of our article: “The article is organized as following. Section 2 presents an overview of current literature and proposes the hypothesis. Section 3 introduces data and methodology, while Section 4 shows the collected results. Finally, Section 5 proposes some conclusions, focusing on the main practical implications…”.

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Comment 3

The literature review must be enriched particularly with recent sources (2019-2022).

Answer 3

Authors have introduced a new section (Section 2 – Literature review and hypotheses), specifying the current background, relative gaps in literature, and justifying our contribution: “…Storm (2021) highlights that Italian interventions has been negatively affected by the fiscal capacity of government to raise spending to cushion the economic impact of the health emergency for vulnerable businesses. Indeed, according to the author, even if the COVID-19 mortality was relatively high, the per-capita spending was relatively low because the high public debt and governments’ limited access to external financial resources. As a consequence, the pandemic had a significant economic negative impact on the national economy. According to Cetrulo (2021), the Italian GDP contracted by about 6.6% between 2019 and 2020, while the reduction in working hours was about 7.5%. Moreover, the author denotes that, compared to 2019, employment declined by 414,000 units (-1.8%), a drop that is mainly concentrated among fixed-term employees (-383,000) and self-employed workers (-129,000). Indeed, the Italian government’s interventions to support economic activities were mainly oriented toward protecting permanent employees, preventing the dismissing of their workers and reducing the cost of unproductive human resources through the introduction of layoff (Gallo and Raitano, 2022). Besides these measures, which significantly reduced the potential uneven impact of the pandemic, preserving job stability for millions of workers (Carta and De Philippis, 2021), there were no interventions to support the demand for final goods and spending by consumers, as well as no significant efforts to support the adoption of new digital services by firms and/or the introduction of innovative products on the market. Moreover, there were limited interventions to support workers’ resilience, facilitating opportunities for smart-working (Tokarchuk et al., 2021)…”.

Cited literature:

Carta, F., & De Philippis, M. (2021). The impact of the COVID-19 shock on labour income inequality: Evidence from Italy. Bank of Italy Occasional Paper, nr. 606.

Cetrulo, A. (2021). Is remote working here to stay? Lessons and ideas for a post-pandemic future. Rivista quadrimestrale dell’INAPP, Anno XI, Vol. 2(2021), 36-49

Gallo, G., & Raitano, M. (2022). SOS incomes: simulated effects of COVID-19 and emergency benefits on individual and household income distribution in Italy. Journal of European Social Policy, forthcoming.

Storm, S. (2021). Lessons for the Age of Consequences: COVID-19 and the Macroeconomy. Review of Political Economy, 1-40.

Tokarchuk, O., Gabriele, R., & Neglia, G. (2021). Teleworking during the COVID-19 crisis in Italy: Evidence and tentative interpretations. Sustainability, 13(4), 2147.

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Comment 4

I have not seen clear defined hypotheses or research questions.

Answer 4

We agree with the reviewer and, accordingly, we have specified our hypotheses in the aforementioned section (i.e., Section 2 – Literature review and hypotheses): “…On the one hand, we expect the adoption of layoff supported the productivity of these firms, decreasing the labor costs while, on the other hand, we expect that their profitability decreased and default probability increased. Hence, following this reasoning, we seek empirical confirmation of a positive relation between access to layoff and productivity but, at the same time, we expect to observe a negative impact on profitability and default probability. More precisely, we expect:

H₁          higher productivity;

H₂          lower profitability;

H₂          higher default probability.

These are exactly the hypotheses that we test in our empirical investigation, expecting to confirm the limits of Italian policy relief during the pandemic. To the best of our knowledge, no investigations have been carried out into the impact of COVID-19 on Italian manufacturing industry, which represents an opportunity to provide new and practical insights to managers and policy makers…”.

___________________________________

Comment 5

The research method is descriptive. The paper would gain value if complex statistical methods were used to establish the relationships between variables (SEM, MANOVA, etc).

Answer 5

According to the comment, authors have proposed an extension analysis to our investigation: “…Finally, in order to corroborate the collected evidence, authors proposes the Multiple Analysis of Variance (MANOVA) as extension analysis. More precisely, MANOVA determines the effects of an independent dummy variable (i.e., equal to 1 if the observation was collected during the COVID-19 pandemic, 0 otherwise) on multiple continuous dependent variables (i.e., Total Factor Productivity, Return On Assets, and the expected probability of default). Hence, we have the opportunity to compare our population of private limited firms – before and after the pandemic – with respect to the multiple continuous variables that represent the managerial dynamics under investigation…”. Table 2 in the manuscript and Table A.2 in the Appendix show the results of this extension.

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Comment 6

Also, a separate discussion section is necessary to show the results of the work in line with the results of other research.

Answer 6

Authors have improved the manuscript, with a sub-section for the discussion of the collected results and the main hypothesis (4.1 Discussion: COVID-19, relief policy and firm dynamics) and a successive sub-section with practical implications according to the collected results (4.2 Practical implications). Finally, we conclude the fourth section with a sub-section that discus the control variables and the collected evidence (Discussion: Firms characteristics and the institutional environment).

Considering the discussion of the results with respect other works, the manuscript has been improved as following: “…Considering current literature, these results are also coherent with some preliminary evidence proposed in the literature and based on the available information collected during the pandemic (e.g., Carletti et al., 2020). Even if the recent COVID-19 crisis has generated a concern that productivity (which was already at historically low levels) may further decline (Furceri et al., 2021), the Italian policy reform was able to maintain high level of productivity, decreasing the labor cost. Nevertheless, on the other hand, the relief policy was not able to support the businesses, with a significant decrease of their profitability and an increase of their default probability. Indeed, according to Del Rio-Chanona et al. (2020), there were demand-side changes due to peoples’ immediate response to the pandemic (e.g., reduced demand for goods or services). Moreover, sectors relating to manufacturing are more likely to be constrained by supply shocks with reductions due to the closure of non-essential industries and workers not being able to perform their activities at home. Our evidence can support these claims, as highlighted by the collected results…”.

In the successive comment we present the practical implications.

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Comment 7

In my opinion, a section of conclusions that includes theoretical and managerial implications, research limitations, and future research directions would be helpful. The current form of the conclusions briefly repeats what was stated in the results and discussion sections.

Answer 7:

Authors agree with the comment, and we have improved the manuscript accordingly.

On the one hand, taking research limitations and future research directions into account, we have suggested that “…Although the results presented here are interesting, our work has clear limits since we focus on a very peculiar case study, i.e., the Italian manufacturing industry, and we have no access to micro data that could corroborate our expectations (e.g., the ability of different occupations to work from home). If new data will be available, our future studies will investigate further these dynamics to corroborate the findings gathered thus far. In addition, if data on other manufacturing industries become available, there will be opportunities to investigate alternative policy reliefs, and to compare different approaches to mitigate next waves…”.

On the other hand, considering practical implications, we have highlighted that “…Practical implications concern the necessary improvements for the above relief policy. In particular, according to results, the introduction of layoff could be integrated with interventions to support the demand of manufactured products. This measure could support the manufacturing industry in this difficult moment, raising their profitability and, in this way, decreasing their default probability. This is an essential measure, as well as highlighted by stakeholders (e.g., CONSOB).[1] Additional interventions could concern the digitalization of services to support the resilience of firms on the market, as well as interventions to support the introduction of innovative products that might respond to new necessity. In both cases, there could be opportunities to make these businesses more competitive on the market, especially in this critical context. Finally, even if the layoff adopted by the Italian government reduced the potential uneven impact of the pandemic, preserving job stability for millions of (fixed) workers, interventions to support the remote working could be advisable, fostering workers’ resilience (e.g., smart-work). Indeed, the possibility of working remotely regards a minority, and it is not equally distributed among the workforce (Cetrulo, 2021). Obviously, the workers excluded by this opportunity could face higher risk of negative outcomes (i.e., lower income or unemployment, as well as worst health conditions), and the pandemic had significantly worsened their conditions. Accordingly, the policy maker should adopt interventions to remove all technical, organizational and social features that might prevent this opportunity…”. These practical implications have been summarized in the last section (Conclusions): “…According to our evidence, practical implications concern the necessary improvements for the above relief policy: interventions to support the demand of manufactured products (I), interventions to support the digitalization of services (II), interventions to support the remote working (III), and finally interventions to support the introduction of innovative products on the market (IV). These interventions could support the Italian manufacturing industry to face potential new waves and/or challenges, creating the necessary conditions for a sustainable economic environment…”.

Note that, coherently with the suggestion of the Reviewer 1, we have adopted a separate sub-section (4.2 Practical implications).

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Comment 8

The article presents some scientific value and can be published after carefully reviewing the reported issues.

Answer 8

Thank you very much for the positive comment. The new version has been improved according to the comments and suggestions, and we believe that both the readability and the robustness of the work have benefited from them. Regardless of your final judgment, the authors would like to thank you for your very useful comments, which have helped us to improve the manuscript.

[1] See Commissione Nazionale per le Società e la Borsa (CONSOB). Link: https://www.consob.it/web/investor-education/crisi-sanitaria-economica

Author Response File: Author Response.docx

Reviewer 4 Report

Tables and text in different formats difficult readings. 

The research methodology is a little bit confussing, and the results are not clear. Some chart or graph should help. 

Conclusions should be stronger, show comparative or something like this. 

Round 2

Reviewer 3 Report

The paper can be published in current form.