How Do Macroeconomic Cycles and Government Policies Influence Cash Holdings? Evidence from Listed Firms in China

Comments 1: Areas for Improvement:

Clarity of Hypotheses: While the hypotheses are generally well-stated, there could be more clarity in distinguishing between the different economic phases (recession vs. boom) and how each specific policy impacts cash holdings during these phases.

Discussion of Results: The discussion of the empirical results could be expanded to provide a deeper interpretation of the findings. For instance, the implications of the positive correlation between economic policy uncertainty and cash holdings during economic prosperity could be explored further.

Literature Integration: While the literature review is thorough, the integration of findings from prior studies with the results of this paper could be strengthened. This would help in situating the current study more clearly within the existing body of knowledge.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have revised these comments as follows.

Clarity of Hypotheses: We have reorganized the hypothesis of the second part and revised both language and logic. Therefore, we revised the part 2.3 “The relationship between economic cycles, economic policy, and cash holdings in listed firms.” in page 4 and page 5, and line 182-221.

“Hypothesis 3a: The phase of the economic cycle influences how monetary policy affects corporate cash holdings. Specifically, during a recession, expansionary monetary policies can help offset the increase in cash holdings, while during periods of eco-nomic prosperity, contractionary monetary policies can help moderate the reduction in cash reserves.

Hypothesis 3b: Stable economic policies can mitigate the negative relationship between economic cycle fluctuations and corporate cash holdings. Specifically, during economic prosperity, stable policies can temper the decline in cash holdings, while during downturns, they can prevent excessive cash hoarding.”

Discussion of Results: We have expanded the discussion section to provide a deeper interpretation of the research findings in page 11 and line 424-439.

“During periods of economic prosperity, companies generally benefit from favorable market conditions and higher profitability. However, when faced with policy un-certainty, corporate managers tend to adopt more conservative financial strategies to ensure sufficient liquidity in an uncertain future environment. Policy uncertainty may manifest as adjustments in tax policies, changes in regulatory environments, and other government decisions that could potentially impact business operations. These uncertainties lead companies to anticipate that the future financial environment might be-come more constrained, prompting them to increase cash reserves to manage potential risks.

In such situations, companies may reduce investments in new projects or delay expansion plans, opting instead to allocate funds to more conservative assets like cash or cash equivalents. The underlying motivation is that by increasing cash reserves, companies can enhance their financial flexibility, allowing them to maintain operational agility in the face of policy changes. This strategy not only helps companies navigate potential financial pressures but also preserves funds for future investment opportunities, enabling them to act swiftly when market conditions improve, or new opportunities arise due to policy changes.”

Literature Integration: We have reorganized the literature and hypothesis of the second part and revised both language and logic. Therefore, we revised the part 2 “Literature Review and Hypothesis” from page 2 to page 5 and line 75-221.

Comments 2: Technical Aspects:

Statistical Analysis: The use of regression analysis is appropriate, but the paper could benefit from additional robustness checks or sensitivity analyses to further validate the results.

Figures and Tables: The tables are informative, but including some graphical representations (e.g., trends over time, interaction effects) could make the data more accessible and visually engaging.

Response 2: Thank you very much for your insightful feedback. We have added additional robustness checks and Figure1. (line 317) to emphasize this point.

“First, the residual analysis reveals that most of the standardized residuals fall within the range of -2 to +2, indicating that the model largely meets the underlying assumptions. This suggests that the regression results are both robust and reliable. Second, to validate the robustness and credibility of the regression results, we replaced the economic cycle variable by employing different calculation methods. While the Mitchell approach is indeed a classical method, contemporary research often incorporates more advanced techniques such as regime-switching models [64-66]. After substituting the explanatory variables, the regression results remained statistically significant, consistent with our initial hypotheses.”

Comments 3: Conclusion and Recommendations:

The conclusions are well-supported by the data, but the paper could benefit from a more explicit set of recommendations for firms operating in volatile economic environments.

The policy implications are well-articulated, but they could be further detailed, particularly in terms of how firms should adjust their cash management strategies in response to different types of government policies.

Response 3: Agree. We have revised the part of Conclusion and Recommendations to emphasize this point in page 13 and line 492-529.

“To mitigate these fluctuations, companies should adopt dynamic cash management strategies that account for changes in the economic cycle, allowing them to maintain optimal liquidity levels across different economic phases.”

“Firms should closely monitor monetary policy signals and adjust their cash holdings accordingly. During periods of restrictive monetary policy or high economic policy uncertainty, companies should increase their cash buffers to safeguard against potential liquidity constraints. Conversely, in times of expansionary policy or stable economic conditions, firms can reduce cash holdings and allocate resources to growth opportunities.”

“Firms need to be proactive in adjusting their cash management strategies based on the combined effects of economic cycles and monetary policies to avoid being caught unprepared during adverse conditions.”

“Therefore, firms must continuously evaluate their cash management strategies, aligning them with current economic cycles and policy environments to enhance operational efficiency and build resilience against future uncertainties.”

Comments 4: Minor Issues:

There are a few instances where the language could be more precise. I recommend a careful review of the manuscript for grammatical errors and stylistic improvements.

The abstract effectively summarizes the paper but could be refined to more clearly highlight the main contributions of the study.

Response 4: Agree. We have revised Abstract to emphasize this point.

“Cash holdings are vital for a firm's resilience and ability to capitalize on investment opportunities amid economic fluctuations. This study investigates the complex relationship between macroeconomic cycles, government policies, and the cash holdings of Chinese listed firms. By analyzing data from Shanghai and Shenzhen A-share listed firms from 2004 to 2019, this research uncovers the individual and combined effects of economic cycles and monetary policies on corporate cash management. Key findings include: (1) A significant negative correlation between cash holdings and economic cycle volatility indicates that firms tend to increase cash holdings during periods of instability and reduce them during economic stability. (2) There is a strong negative relationship between restrictive monetary policy and cash holdings, suggesting that firms accumulate more cash to safeguard against tighter financial conditions. (3) The interplay between economic policies and business cycles reveals that during recessions, restrictive monetary policy increases cash holdings, while economic policy uncertainty reduces them. In contrast, during economic prosperity, monetary policy has minimal impact on cash holdings. These insights emphasize the need for firms to integrate both economic cycles and policy environments into their cash management strategies. The findings offer valuable guidance for policymakers and business leaders aiming to enhance financial stability and optimize cash holdings across different economic conditions.”

Comments 1: It is interesting that you have chosen to use the Mitchell approach to categorising business cycles. While the Mitchell approach is classical many papers would also consider more modern approaches in the form of regime switching models, see inter alia Filardo (1994) and Kim and Nelson (1998), and for a recent Chinese paper see Wang et al (2023). Perhaps you need to explore both methods as a robustness check on your analysis.

References

Filardo, A. (1994), Business-Cycle Phases and Their Transitional Dynamics, Journal of Business and Economic Statistics 12, 299-308.

Kim, C. and Nelson, C. (1998), Business Cycle Turning Points, A New Coincident Index, and Tests of Duration Dependence Based on a Dynamic Factor Model with Regime Switching, Review of Economics and Statistics 80, 188-201.

Wang, X., Sun, Y. and Peng, B. (2023), Industrial linkage and clustered regional business cycles in China, International Review of Economics & Finance 85, 59-72.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have added this part in page 12, paragraph 2 in Robustness test, and line 478-484. Economic cycles serve as a crucial explanatory variable in this study, reflecting a long-standing area of scholarly focus with methodologies for their measurement and calculation continuously evolving. In this research, we employed GDP quarterly growth rate percentiles to delineate economic cycles—a method that is both straightforward and representative. In response to the reviewer’s suggestion, we further incorporated regime-switching models as a robustness check to enhance the rigor of our analysis. The consistency of the results obtained after substituting the explanatory variables with those of the main regression underscores the robustness of our findings. This methodological refinement has significantly bolstered the study's credibility and overall persuasiveness.

“Second, to validate the robustness and credibility of the regression results, we replaced the economic cycle variable by employing different calculation methods. While the Mitchell approach is indeed a classical method, contemporary research often incorporates more advanced techniques such as regime-switching models [64-66]. After substituting the explanatory variables, the regression results remained statistically significant, consistent with our initial hypotheses.”

Comments 2: The main results are presented in tables 4 and 5 but with no regression diagnostics. You need to add appropriate regression diagnostics to determine if your models are appropriate.

Response 2: We have revised this part page 12, paragraph 2 in Robustness test, and line 476-478 to emphasize this point. Regression diagnostics play a critical role in validating linear regression models by detecting outliers and influential data points that could skew the results. These diagnostics are crucial for verifying whether the underlying assumptions of the model are met, thereby affirming the appropriateness of the model selection. Key diagnostic tools, such as residual analysis, tests for heteroscedasticity, and checks for multicollinearity, provide a comprehensive evaluation of the model's performance. By integrating additional residual analysis, this study enhances the robustness and credibility of the chosen models.

“First, the residual analysis reveals that most of the standardized residuals fall within the range of -2 to +2, indicating that the model largely meets the underlying assumptions. This suggests that the regression results are both robust and reliable.”

4. Response to Comments on the Quality of English Language

Point 1: English language fine. No issues detected.

Response 1: Thank you for your positive feedback regarding the quality of the English language in the manuscript. We appreciate your thorough review and are glad that the language meets the required standards.

Comments 1: It is OK now.

Response 1: Thank you for your positive feedback. We are glad that the revisions have addressed the concerns, and we appreciate your time and effort in reviewing our paper.

Comments 1: Thanks for revising the paper in response to the comments and adding the robustness test details in section 4.6. To better understand the robustness of the results could you please add some additional text to explain the similarity in the results in terms of whether that is driven by consistent classification of the dates for economic prosperity versus recessions based on the different classification methods (in other words what % of dates change classification) and/or similar parameter estimates (and statistical significance) even when there is a change of dates. This detail would enable the reader to better understand the key factors in the robustness of the results.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have added this part in page 12, paragraph 2 in Robustness test, and line 484-489. Thank you for your valuable feedback. In response to your suggestion, we have added further explanation in section 4.6 regarding the similarity in the results obtained from different classification methods for economic prosperity and recessions. Specifically, we clarified that while there are minor discrepancies due to the different measurement approaches, the overall trend in the economic cycle remains consistent, as indicated by a high correlation coefficient of 0.91 between the two methods. Additionally, we highlighted that even when the classification of dates differs, the parameter estimates and their statistical significance remain robust. This additional detail should provide a clearer understanding of the robustness of our findings and the key factors driving the consistency of the results.

“Although the measurement methods for economic cycles vary, both approaches yield only minor discrepancies, with the overall trend of economic cycles remaining largely consistent. The correlation between the two methods is notably high, with a coefficient of 0.91. As a result, even when different measurement techniques are employed, the parameter estimates and their statistical significance in the regression results continue to demonstrate robustness and reliability.”