Macroeconomic policy and profit rate of a company: A dynamic panel estimation and comparative analysis from Indonesia

Macroeconomic policy (fiscal and monetary) dynamics are interesting to analyze, especially considering corporate performance. This paper aims to determine the effect of macroeconomic policy on the company’s profit rate. Effectiveness of tax revenue (ETAX), realization of tax revenue (RTAX), Bank of Indonesian rate (BIRT), investment growth (INVG), realization of investments (RINV), infrastructure fund allocation rate (INFR), and realization of infrastructure funds (RINF) are macroeconomic policy variables. This study uses a sample of 256 companies listed on the Indonesia Stock Exchange (IDX) in 2005–2019. This paper employs such methods as GMM, using Wald-test and Sargan’s test. GMM estimator result shows that the instrument of infrastructure fund realization policy (RINF), investment growth (INVG), and investment realization (RINV) affect the company’s profit rate (PROF). Therefore, companies need to pay attention to the government development plans, investment growth, and investment realization, which can improve company performance. The result, government’s development for the 2005–2009 and 2015–2019 periods shows a significant difference in companies’ ability to generate profits.
AcknowledgmentsWe would like to thank the Department of Management, Faculty of Economics and Business, Universitas Islam Nahdlatul Ulama Jepara (Unisnu), and the Institute of Research and Community Services (LPPM) Unisnu Jepara Indonesia, which has supported this study.

INTRODUCTION
A company's profit rate is a widely researched topic. Empirical study indicate that internal or external factors can determine company profitability (Eljelly, 2013;Jadah et al., 2020). Profitability is usually measured using financial ratios such as net profit margin, gross profit margin, return on asset, return on investment, and others (Brigham & Houston, 2016). Several empirical studies examine factors that affect a company's profit rate internally, such as financial ratios, solvency, activity, liquidity (Ermy & Bambang, 2019), non-financial factors, firm size (Margaretha & Supartika, 2016), and corporate governance (Ararat et al., 2017). Jadah et al. (2020) proved that macroeconomic factors that affect the profit rate include economic growth, government effectiveness, inflation, interest rate, unemployment, and political instability. However, it is crucial to test the impact of infrastructure development on a company's profit rate.
Infrastructure development is one of the critical foundations of economic growth (Familoni, 2006; Owusu-Manu et al., 2019; Patra & Acharya, 2011). However, infrastructure is often analyzed for macroeconomic activities, while its influence on company performance has not been studied in Indonesia. For example, McCawley (2015) de-scribes the development and managerial barriers of infrastructure in Indonesia over the past five decades. In contrast, Makmuri (2017) identifies the influence of infrastructure instruments in the distribution of revenues. Recently, Maryati et al. (2020) analyzed infrastructure development benefits for the agricultural sector.
Infrastructure is a basic need in improving the investment climate. Infrastructure improvements lead to an increase in the state financial budget. Thus, tax revenue policy has an impact on company expenses. A company became the object of the country that felt the most impact from every policy set by the government because the largest tax contributions came from the processing industry sector (31.8%), trade (19.3%), and financial services (14%) (Ministry of Finance RI, 2018). Increasing state revenues improve the investment climate in the business world and can optimize economic potential and improve tax reform measures. Dollar et al. (2005) analyzed an important investment climate for productivity levels, wages, profit rates, production growth rate, employment, and capital stock of companies. The role of government is critical for companies in providing an excellent regulatory framework for infrastructure, international market access, and financial services. The key to the progressive socio-economic development of society is an investment by regulating a favorable investment climate (Sibirskaya et al., 2015). A better investment climate leads to higher returns on equity. Higher returns on equity will lead to faster company capital accumulation and growth. However, a low return on equity reduces company profitability and shows a slow growth rate.

LITERATURE REVIEW
The economic state of a country significantly affects the trade cycle, either domestically or internationally. Trade in the economic cycle does not escape the productivity level of a company. The productivity of goods and services produced at all times will determine the standard of living by looking at the total revenue and total costs obtained from the company's economic activities (Mankiw, 2020). Planning the management of the company's funds for production or investment (both short-term and longterm investments) must be realized by economic conditions to survive in all economic situations. Tax policy from the government will affect the ups and downs of a company's profit. The company's profit is affected by the tax imposed. If a company incurs the greater tax, it will lead to a decrease or smaller prediction of net profit (Beigi et al., 2013).
Deferred tax expense has a positive and significant effect on profit management. The higher the deferred tax burden, the greater the company's profit management to avoid losses (Kasipillai & Mahenthiran, 2013). On the other hand, when taxes are included as deductions in the company's financial statements, it reduces its net profit. Therefore, the government's tax rate policy significantly affects the profit rates generated by companies. The profit rate is a measure of the company's profitability that describes the condition of a company, whether growing, stagnant, or falling. These variables are negatively related to the profitability of banks in China (Tan, 2016) and go-public companies on the Bucharest Stock Exchange (Vătavu, 2014). The more taxes companies pay, the higher the tax burden, thus lowering profitability. Schoenmaker et al. (2014) also pointed out that local taxes have a negative impact on the profitability of the Flemish hospitality industry.
Literature and empirical studies provide some theories that demonstrate the relationship between monetary policy and projected business performance with various macroeconomic variables. To test the influence of monetary policy on the performance of manufacturing sector companies, Imoughele and Ismaila (2014) found that the performance of manufacturing companies in Nigeria is very responsive to monetary instruments established by authority. The significant relationship is reflected in variable inflation, exchange rates, and external reserves. In contrast, the amount of money in circulation and interest rates are inactive in concluding monetary policy to the manufacturing sector. Different results were shown by Osakwe et al. (2019). Interest rates were found to be an effective monetary policy tool to the performance of manufacturing companies in Nigeria. Monetary policy effects are also seen in capital market performance. Isola and Mesagan (2018) observed the influence of monetary policy on the performance of SMEs in three countries in West Africa. It was concluded that monetary instruments of interest rates and loans to the private sector significantly affected Nigeria but had no effect on Ghana. On the other hand, the exchange rate affected the performance of SMEs in all three countries. Therefore, monetary policy determines the company's decision to maintain liquidity and avoid higher financial stability risks.
Infrastructure allocation funds are increasing along with the development of a country's economy. Infrastructure development is important for human resource development and economic growth (Tsaurai & Ndou, 2019), both the construction of electricity distribution infrastructure (Palei 2015), mobile (Toader et al., 2018), transportation (Mohmand et al., 2017), to road construction and repair (Ivanova & Masarova, 2013). Indonesia's infrastructure budget comes from the general allocation fund. General allocation funds are funds used to finance the needs of provinces and districts/cities in the framework of decentralization implementation. This fund continues to increase every year along with Indonesia's increasingly advanced economic cycle.
McCawley (2015) described infrastructure development in Indonesia from 1965 to 2015. As a result, he mentioned that infrastructure experienced significant development, but the quality is often complained about due to poor maintenance and management. On the other hand, demand for infrastructure is very high, and infrastructure issues limit market and economic activities due to access that can be difficult. As a result, infrastructure problems often lead to income inequality (Makmuri, 2017). By analyzing 32 provinces during 2007-2013, Makmuri (2017) found infrastructure facilities in the form of electricity quantity, quantity, and airport quality, encouraging income distribution and reducing income inequality.
The investment climate in various countries is created from domestic direct investment (DDI) and foreign direct investment (FDI) activities. Concerning the economic sector, FDI and DDI are proven to affect economic growth in various countries (Bayar, 2014;Lean & Tan, 2011;Mohamed et al., 2013). On the other hand, foreign direct investment and direct domestic investment complement each other in cre-ating an investment climate that can encourage investment and maintain economic growth (Ullah et al., 2014). In addition, Kubny and Voss (2014) mentioned that FDI can provide investment opportunities to local companies through the provision of technology that cannot be produced domestically.
The combination of FDI and DDI plays a vital role in increasing entrepreneurship (Munemo, 2014). Shawa et al. (2014) ensured that FDI is important for predicting foreign investment inflows in the economy, and the increase in FDI positively impacts export growth. It is known that domestic investment positively impacts export growth (Tien, 2016). A study was conducted in the United States to evaluate the causal relationship between the origin of the investment and company performance. Chen (2011) indicated that the company received FDI showing better performance than companies that received acquisitions from domestic. Companies receiving foreign investments experienced increased profits, higher sales and labor productivity. Thus, investment creates a financial atmosphere that can affect company profitability.
From the factors described previously, this study aims to explore the influence of several government policies (fiscal and monetary) on the profitability of companies in Indonesia. The policy instruments include tax revenues, interest rates, allocation of infrastructure funds, and investment. There are two interesting things to analyze in this study. First, the impact of economic policy on issuers' performance is analyzed, where economic policy will affect their performance. Second, it is vital to determine the effect of each policy on the three main sectors of public companies in Indonesia listed on the stock exchange in three main sectors. They include the primary sector, industrial and manufacturing sector, and the tertiary sector (services). Moreover, the paper aims to indicate the differences between these three sectors because each sector has its own character.

METHODOLOGY AND DATA
The empirical specification of this study is based on the type of research data used. Panel specifications allow for a degree of cross-company het-erogeneity, as the influence of fiscal policy and monetary policy on a company's profit rates can vary between companies. The paper tries to record the dynamic process between fiscal policy, monetary policy, and corporate profit rates in Indonesia.
The study used the dynamics of the data panel; in more detail, the econometric model estimated in this study can be written in Equation 1 (Teixeira & Queirós, 2016): where PROF i,t is lag of dependent variable, denotes the profit rate, ETAX i,t is lag of effectiveness of tax variable, RTAX i,t is lag of tax revenue variable, BIRT i,t is lag of interest rate proxied with BI-rate, INFR i,t is lag of infrastructure fund allocation rate, RINF i,t lag of realization of infrastructure funds, INVG i,t is lag of investment growth, and RINV i,t is lag of realization of investments.
The Wald-test is used to test the explanatory power of independent variables on dependent variables. While validity is analyzed using the Sargan's test with a significance of 0.05, whose null hypothesis is that over-identifying restrictions are valid.

Variable instrument and data sources
The study used four different panel data sets to estimate dynamic models. The data set is based on the industrial sector of go-public companies listed on the Indonesia Stock Exchange (IDX Measurement of research variables is projected based on the adoption of the literature and previous research (Table 1). For measuring a dependent variable of profit rates, the study used one formula from Brigham and Houston (2016): net profit margin. The measurement of the effectiveness of tax revenues adopts the formula used by Ruliana (2015), which is the comparison of receipt realization to the revenue target. BI rate is the interest rate set by the Bank Indonesia. The infrastructure fund allocation rate formula adopts the common size ratio of Ehrhardt and Brigham (2013). Data on the amount of state tax revenue and infrastructure allocation funds are obtained from the Government Financial Report from the Ministry of Finance of the Republic of Indonesia. As for investment growth, it is measured by modifying the growth ratio of Zheng et al. (2015). Economic sector investment realization data is obtained from the Indonesian Central Statistics Agency database. To identify correlations between research variables and see the magnitude of co-movement, the correlation matrix is displayed in Table 3. In the end, the correlation matrix value of each variable indicates that there is no correlation of each research variable.

EMPIRICAL RESULTS
The GMM estimator assumes the data is stationary. However, sometimes in one data set the panel is found not stationary. Thus, the root testing unit is considered. The study used four root unit testing methods: Levin-Lin-Chu test, Im-Pesaran-Shin test, Phillips-Perron (PP) Fisher test, and Augmented Dickey-Fuller (ADF) Fisher test. After passing the root unit test, it was concluded that the variable profit rate in each sector was stationary (probability < 0.05) with the results in Table 4.
Once it is determined that the stationary assumption in the regression analysis is not violated, then the GMM estimator regression results are accepted. The study presents four dynamic regression results of the GMM estimator panel for each dataset, along with the results of the Wald test and the Sargan's test. Manufacturing sector data set

Stat.
Prob. Note: Set 1 -is all data sets; Set 2 is primary sector dataset; Set 3 is manufacturing sector dataset; and Set 4 is service sector dataset.  icant. The realization of infrastructure fund allocation affects the profit rate of the primary sector company.

Factors affecting the profit rate of the manufacturing sector
Dynamic panel analysis should be performed when the lag of dependent variables is used to estimate unbiased estimators. The study found that BIRT, INVG, and RINV were significant to profit rates in manufacturing sector companies. The Wald test reinforces this result and the straightforward Sargan's test that independent variables can explain dependent variables well, and over-identifying restrictions are valid.

Factors affecting the profit rate of the service sector
A company's profit rate in the service sector is influenced by the INVG and RINV variables which are one instrument of fiscal policy. This statistical result (Table 8) found no significance of the variables in the model even though the Wald and Sargan's tests were clear.

Comparison of the firm's profit rate in both cabinets
Countries around the world inevitably experience shifts in heads of state with certain leadership styles and controversial policies. The difference between two or more leaderships in a country can bring good news or create a dilemma for entrepreneurship (large or small companies). Differences in economic policy between governments impact the company's profit rate; the study analyzed the difference in corporate profitability between the two Indonesian governments. The two governments are called Cabinet 1 and Cabinet 2. Cabinet 1 was the government in 2005-2009, while Cabinet 2 was the government of the period 2015-2019. Based on the two samples, the t-test in Table 9 indicates a significant difference in the corporate profit rates in Indonesia between the two cabinets (p < 0.05). However, the difference is very thin because the probability value is close to 0.05.
Bonferroni tabulation is required to know whether or not there is a difference in profit rates in three industrial sectors in each cabinet. The statistics  are presented in Table 10. The study found no difference in profit rates between the industrial sectors of companies in Indonesia in both reigns (p > 0.05). Bartlett's test also conveys a probability value of 0.000 less than the critical value. All three sectors in both cabinets had the same variant.

DISCUSSION
The analysis of dynamic panel estimators on this study obtained surprising results. The profit rate of companies listed on the Indonesia Stock Exchange is generally determined by fiscal policy instruments. The policy instrument is the realization of infrastructure funds, investment growth, and investment realization. All three play different roles. The study looked at that the realization of infrastructure funds and investment growth lead positively to an increase in the company's profit rate, while investment realization has a negative influence. The realization effect of infrastructure funds is also seen in the primary sector. These findings support Makmuri (2017): improving infrastructure facilities can drive income distribution and reduce inequality. Although, the realization of infrastructure is not felt significantly by the manufacturing and service sectors individually, but it is overall significant. Equitable infrastructure provides mobility for people and businesses in particular to support operational activities and distribution of products/services. Agriculture and mining companies need infrastructure and mobility support for the production and delivery of goods. As Obayelu et al. (2014) and Maryati et al. (2020) found, infrastructure encourages farmers to save time and costs, resulting in higher profit-generating capabilities.
The influence of investment growth and investment realization is also found in the manufacturing sector and service sector. Investment growth has a positive impact on the profit rate of manufacturing sector companies, while in the service sector shows a negative direction. The findings support Ullah et al. (2014), who found that DDI and FDI create an investment climate that can encourage investment. Investment growth shows a climate that encourages manufacturing companies to invest through the provision of technology to support productivity and increased revenue. Most manufacturing companies in Indonesia export goods to several countries. This shows that good investment growth can increase the growth of the company's exports so that their performance increases.
On the other hand, the service sector feels the opposite influence. The realization of investment negatively influences the company's profit rate, both in the manufacturing and the service sectors. There is a favorable investment climate when domestic investment and foreign direct investment complement each other. The study saw that the proportion of FDI realization is much higher than DDI. DDI is half that of FDI; even in 2008 DDI was only 14%. When higher FDI cre- ates a more competitive business environment and disrupts domestic products/services, domestic products/services will compete with foreigners, impacting their performance (Chen, 2011).
The study found that the interest rate projected with BI rate is insignificant to the company's profit rate both in the primary sector, service sector, and overall. The effect is only shown in the manufacturing sector. BI rate is the monetary policy instrument used in this study. This instrument was found to have a positive influence on the profit rate of manufacturing companies in Indonesia. That is, the interest rate set by Bank Indonesia affects the profit rate of manufacturing sector companies. Interest rates are often related to capital markets and money circulation (borrowing and saving). Companies tend to save funds to suppress cash outflows, increase their output, and avoid greater interest charges due to increased interest rates (Isola & Mesagan, 2018).

CONCLUSION
Government policy at the time of the pandemic influenced the economic condition of a company. This study aims to analyze the effect of macroeconomic policy on company's profit rate in Indonesia. The research findings explain that the policy instruments for infrastructure fund realization, investment growth, and investment realization affect the company's profit rates. The impact of investment policy on profit rate is also seen in the manufacturing and service sectors, although it shows a different direction in the investment growth variable. Meanwhile, the realization of infrastructure funds only affects the profit rates of primary sector companies. On the other hand, monetary policy only affects the profit rates of manufacturing sector companies. The different tests show a significant difference in the mean of profit rates in the two government cabinets, the period 2005-2009 and the period 2015-2019.
The dynamic results of the relationship between fiscal policy and monetary policy on the corporate profits rates in Indonesia can open the horizons of readers, state officials, and company management in making decisions. The Indonesian government can pay close attention to economic policy instruments (fiscal and monetary) because of the impact on business performance in Indonesia. Future research can further examine the involvement of macroeconomic policies on company performance, such as distinguishing between the roles of FDI and DDI, inflation, currency exchange rates, and other macroeconomic instruments.


Exposure to the COVID-19 pandemic environment and generosity

We report data from an online experiment which allows us to study how generosity changed over a 6-day period during the initial explosive growth of the COVID-19 pandemic in Andalusia, Spain, while the country was under a strict lockdown. Participants (n = 969) could donate a fraction of a €100 prize to an unknown charity. Our data are particularly rich in the age distribution and we complement them with daily public information about COVID-19-related deaths, infections and hospital admissions. We find correlational evidence that donations decreased in the period under study, particularly among older individuals. Our analysis of the mechanisms behind the detected decrease in generosity suggests that expectations about others' behaviour, perceived mortality risk and (alarming) information play a key—but independent—role for behavioural adaptation. These results indicate that social behaviour is quickly adjusted in response to the pandemic environment, possibly reflecting some form of selective prosociality.

1. The manuscript has minor spelling/ grammatical errors (e.g., use of different tenses in the same paragraph, plural vs. singular nouns and verbs). While this is not a significant issue (as these are issues I also commonly run into in my writing), I found myself distracted by these instances and unable to focus on the authors' argument. I feel that the authors would be able to address these instances with another read-through of their manuscript.
2. In the abstract, it would help to have a little more precision and clarity. For example, why not use the exact number of participants instead of a rounded approximation? Why not separate the results to state their importance clearly? Why not list that solidarity and empathy are the "social preferences" that are studied? As is, it feels like the reader needs to have read the manuscript in its entirety to fully understand and appreciate the work the authors present in the manuscript.
3. I'm not sure if it was in the submission process or conversion to a PDF for reviewers, but the version of the manuscript I received had not indentations for paragraphs. This was highly distracting, as there were multiple places in the manuscript where it appeared as if paragraphs went on for pages and switched topics in numerous sites. It would help (if only for the sake of reviewing) to make sure that new paragraphs are indicated with indentations or lines between paragraphs.
4. I found the introduction to be a little simplistic in its presentation of information. While the studies and topics that the authors mention are interesting, it feels as if the authors assume that their readers have read the same primary sources and do not need a detailed explanation of the studies, variables, and topics presented as the rationale for their research. Examples of this include: "Indeed, CamposMercade et al. (2021) report a positive correlation between people's prosociality and health behaviors during the pandemic.", "Not surprisingly, scholars across the behavioral sciences call to emphasize the impact of one's own actions on the well-being of others while designing and communicating public health campaigns (Van Bavel et al., 2020) and many campaigns in fact do so." While the authors say these references support their rationale, it is not clear to me as a reader how they support it. What variables, outcomes, and conclusions from these articles lead them to study generosity? I needed to refer to these citations and briefly skim the articles to understand their rationale fully. Since this isn't practical for other readers, it would help if more information about these citations were given in the introduction to fully set up the rationale for the study.
5. The authors try to claim that their results speak to selfish vs. prosocial responses in their sample. But, this is only one explanation for their results. It is also possible that the participants are employing selective generosity that their results are not able to capture -for example, it is possible that participants would have been more likely to be generous with romantic partners (Lukaszewski and Roney 2010), friends (Krems et al. 2021), or those in their community who need their help or with whom the participant pools their risk (Aktipis 2016;Cronk et al. 2019;Cronk et al. 2019). None of these alternative explanations discount the work and conclusions drawn by the authors, but to state that their work addressed participants who lack "intrinsic motivation" to behave selflessly during this time is not accurate.
6. More explanation is needed in the introduction to set up the later use of solidarity and envy as social preferences that may influence generosity in this sample. From my reading, there is only one paragraph (on page 4) that focuses on "observed" signs of solidarity and anti-social behaviors, but there is a lack of citations to relevant literature (such as Mesurado et al. 2021;Dinić and Bodroža 2020;Buso et al. 2020), so the reader is asked to take the authors' word on this. More explanation, and nuance of how this may manifest, is needed. 7. The paper describes the study's objectives (3), but does not provide concrete and testable hypotheses that they have designed the study to test. If the study is exploratory (as I suspect it is), that is perfectly fine, but the authors should 1) state that the study is exploratory and 2) detail the potential outcomes for their objectives and what the outcomes would mean for generosity during the pandemic (i.e., that people were more or less generous during the lockdown).
8. The authors state: "We thus ask whether generosity changes differently across people depending on the true vs. perceived Covid-19-associated mortality" But, having read through the manuscript, it is not clear how they do this. Making the operationalization of these concepts and the subsequent hypothesis and meaning transparent would help readers feel guided through this part of the experiment.
9. The structure of the paper would be significantly improved if the authors implemented a more traditional introduction-method-results-discussion and conclusion format. The interpretation and implications of the results are currently presented in tandem with previous research in the introduction and, to put it plainly, this format makes it hard to follow the logic that motivated the current study. By interpreting the results in the introduction (before the reader has had a chance to read and evaluate the results for themselves; pages 5 -8), the reader just has to trust that they would interpret the results similarly. For example, statements like: "The decreased generosity detected in our study might partially explain these results.", "While our results are in line with the latter evidence, all these findings indicate that social behavior adapts following a complex pattern and that both short-term and long-term dynamics need to be considered separately.", "Last, as mentioned above, Campos-Mercade et al. (2021) report correlations between social preferences and health behaviors, highlighting the importance of our findings for the effectiveness of frequent public recommendations and policies appealing to human otherregarding concerns during the pandemic." imply that the reader already knows the results and can assess the accuracy of these claims for themselves, something that is not possible in an introduction before results are shown. The discussion of the results (pg 5 -8) is more important for a discussion section, though many of the ideas and descriptions need more explanation for readers to assess them easily.
10. Throughout the manuscript, the authors refer to one variable as "contagion" and "cases." It would be best to refer to the same variable by a single term, and "cases" is probably the most accurate (since the variable reports the number of cases in Spain for that day).
11. The methods section mentions that participants were incentivized to further recruit participants -how was this done? 12. As far as the method section describes, this study was co-opted for this purpose (i.e., it was originally planned for another purpose). If this is not the case, the writing needs to be clearer to describe how the authors made the study in response to the announced lockdowns. Currently, the impression is that students were already participating, and the purpose of the study changed once the lockdown was announced (which calls into question whether a sensitivity analysis or a priori power analysis is needed -It is currently also unclear which the authors present here).
13. When the authors talk about their balanced sample, it is a little unclear if they mean balance between the March 20-22 and March 23-25 groups or balanced in terms of generalizability to the overall Spanish population.
14. It is unclear what the experimental earnings are and how they were converted into lottery tickets (e.g., is 1 euro = 1 lottery ticket?; how much did people earn on average?).
15. There are many potential DVs mentioned in the text that are not fully described in the resultswhere are the results of the cognitive reflection, risk preferences, loss aversion, time preferences, stag hunt, and Big -5 variables? The manuscript says all other variables, but that doesn't give enough information.
16. It would be very helpful to discuss the overall regression analysis results (and type of regression used) in the text on page 12 instead of directing the readers to the table for the information.
17. The kinds of coefficients reported needs to be more explicit. Regression analysis gives both standardized and unstandardized coefficients, and there is nowhere in the text that specifies what coefficient the authors are interpreting & comparing across models (though, hopefully, it is the standardized coefficients).
18. Results, coefficients, standard errors, and p values jump between percentages and decimals. Please pick the format you intend to use for these variables and make it consistent throughout the manuscript.
19. Please give the coefficients/ effect sizes for the effects described -giving p-values does not give the reader enough information to assess the size of the effect beyond saying that the effect exists (which is not surprising given the large sample). I noticed this starting on page 14. 20. It is very odd to report results that are coming from another preprint (page 14, footnote 12), and I am not sure this inclusion buys the authors much in terms of explanations as it is not fully clear why this other analysis from the same data but in another paper is necessary. My reading of this part was that there wasn't a massive influence of day x age when controlling for day x expectations, but it is important enough to be in another paper, so it seems like the authors are misleading the reader as to somethings else regarding this analysis that could be important. Since I do not think this is the authors' intention, it might be best to add this as a footnote or completely omit it from the current manuscript. 21. It would be helpful to know the kind of coefficients for tables 1 & 2, and to specify that the numbers in parentheses mean SE. It is also unclear what "Province FE" refers to.
22. There were a lot of tests in this manuscript but no mention of corrections for multiple tests. It would be helpful for the authors to mention which of these effects survive correcting for multiple tests.
23. It is unclear why the authors begin referring to solidarity and envy as "SR-solidarity" and "SR-envy" as all of their data is self-report (even the donations). There are no objective measures in this study simply because the experiment was conducted online while people were stuck at home. In addition, the authors have some rationale in the introduction as to why they thought solidarity and envy would be important, but it is still not clear why these measures and not others were used. 24. The authors state " The moderation effect of age on giving is robust to controlling for selfreported solidarity and envy though." but it is not clear what analysis the authors are referring to as Table 1 suggests envy and solidarity were in separate models and outcome variables.
25. I believe that the authors mean that exposure to public information (e.g., deaths, cases, ICU patients) causes donations to decrease. Still, the wording "donations scale down" implies that the donations decrease in a scaleable form as more access/ exposure to information is included in the model. As that is not how table 2 presents the data, more clarity is needed here.

26.
It is unclear what the authors mean with "Shachat et al. (2020) perform a longer time horizon analysis in Wuhan, China and find long-term increases in prosociality after a decline in the immediate aftermath of the city lockdown. Our findings are consistent with such a pattern and, together, suggest that the behavioral adaptation process may follow complex dynamics." pg 20. The "behavioral adaptation process" aspect is not clear -do you mean changes in prosociality?
27. This section is also not clear (pg. 20) "The results would also have broader implications for the building of social resilience to future disasters, for which large-scale collective response is as important as for the Covid-19 pandemic. Such challenges are numerous (Boyd et al., 2018)." 28. By this point in the discussion, the effects of age are referred to as moderating effects -but this language was not used in the results section. It would be helpful to call the age effects similar things across all sections of the paper (for consistency from the reader's perspective, I had to go back and make sure the effect was a moderation effect instead of something else).
29. Toplak et al. is missing from the reference section.
30. I'm not sure if I missed it in my download, but I did not have access to the Appendix. I also was not able to access the link to the anonymous data file from the link provided.
While my critiques of the manuscript seem numerous, I would like to reassure the authors that this is only the case because I firmly believe there are many more positive aspects of the manuscript than things I can critique. My main concern primarily deals with the framing of the manuscript, which is why I have suggested a major revision. We hope you are keeping well at this difficult and unusual time. We continue to value your support of the journal in these challenging circumstances. If Royal Society Open Science can assist you at all, please don't hesitate to let us know at the email address below.

Dear Dr Kovarik
The Editors assigned to your paper RSOS-210919 "Exposure to the Covid-19 pandemic and generosity" have now received comments from reviewers and would like you to revise the paper in accordance with the reviewer comments and any comments from the Editors. Please note this decision does not guarantee eventual acceptance.
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I am therefore especially grateful to the two Reviewers, both experts on the topic, who provided thorough evaluations. They are both enthusiastic about your research, and I share their positive views. The comments range from somewhat major (e.g., relevant literature and theoretical rationale) to more minor (e.g., typos and formatting) and I suggest you attend to them as much as you can. You will find the relevant points in the reviews below, which are self-explanatory so I will not repeat them here.
Please note that the journal's default revision time is rather short, but it would be completely acceptable if you wanted to take longer to revise the paper, to make it as strong as possible. I look forward to receiving the revision in due time.
Sincerely, Simone Schnall Associate Editor

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Reviewer comments to Author: Reviewer: 1 Comments to the Author(s) See attached file.
Reviewer: 2 Comments to the Author(s) Review of "Exposure to the COVID-19 pandemic and generosity" Manuscript ID: RSOS-210919 In this paper, the authors describe how the COVID-19 pandemic affected generosity in Spain during the first six days of the national lockdown (March 20-25). The authors are specifically interested in determining if generosity (as indexed by donations to a charity) increased or decreased in this population during the slow burn crisis. The authors' analyses suggest 1) donations decreased over the study period, 2) access to information regarding the health impact of the pandemic (cases, deaths, number of people in the ICU) was also associated with decreased generosity, and 3) this was particularly true for older individuals in their sample.
I believe that the main points of this manuscript are interesting and assess an impactful research question (i.e., do slow-burn disasters impact the generosity of those who experience them). As the authors state, their analyses are primarily correlational but represent an essential step towards understanding the nature of generosity during pandemics and how this generosity (or lack thereof) has important implications for public health policies and national responses to the pandemic. However, I do have reservations about the publication of the manuscript in its current form. Primarily, my concerns center on the structure of the manuscript, lack of clarity in certain parts of the manuscript, and the need for a more thorough explanation in other parts of the manuscript. I feel confident that the authors would be able to address these comments with a major revision of their manuscript.
Below I provide additional details about each of my suggestions, enumerated for ease of communication during the review process: 1. The manuscript has minor spelling/ grammatical errors (e.g., use of different tenses in the same paragraph, plural vs. singular nouns and verbs). While this is not a significant issue (as these are issues I also commonly run into in my writing), I found myself distracted by these instances and unable to focus on the authors' argument. I feel that the authors would be able to address these instances with another read-through of their manuscript.
2. In the abstract, it would help to have a little more precision and clarity. For example, why not use the exact number of participants instead of a rounded approximation? Why not separate the results to state their importance clearly? Why not list that solidarity and empathy are the "social preferences" that are studied? As is, it feels like the reader needs to have read the manuscript in its entirety to fully understand and appreciate the work the authors present in the manuscript.
3. I'm not sure if it was in the submission process or conversion to a PDF for reviewers, but the version of the manuscript I received had not indentations for paragraphs. This was highly distracting, as there were multiple places in the manuscript where it appeared as if paragraphs went on for pages and switched topics in numerous sites. It would help (if only for the sake of reviewing) to make sure that new paragraphs are indicated with indentations or lines between paragraphs. 4. I found the introduction to be a little simplistic in its presentation of information. While the studies and topics that the authors mention are interesting, it feels as if the authors assume that their readers have read the same primary sources and do not need a detailed explanation of the studies, variables, and topics presented as the rationale for their research. Examples of this include: "Indeed, CamposMercade et al. (2021) report a positive correlation between people's prosociality and health behaviors during the pandemic.", "Not surprisingly, scholars across the behavioral sciences call to emphasize the impact of one's own actions on the wellbeing of others while designing and communicating public health campaigns (Van Bavel et al., 2020) and many campaigns in fact do so." While the authors say these references support their rationale, it is not clear to me as a reader how they support it. What variables, outcomes, and conclusions from these articles lead them to study generosity? I needed to refer to these citations and briefly skim the articles to understand their rationale fully. Since this isn't practical for other readers, it would help if more information about these citations were given in the introduction to fully set up the rationale for the study.
5. The authors try to claim that their results speak to selfish vs. prosocial responses in their sample. But, this is only one explanation for their results. It is also possible that the participants are employing selective generosity that their results are not able to capture -for example, it is possible that participants would have been more likely to be generous with romantic partners ( . None of these alternative explanations discount the work and conclusions drawn by the authors, but to state that their work addressed participants who lack "intrinsic motivation" to behave selflessly during this time is not accurate. 6. More explanation is needed in the introduction to set up the later use of solidarity and envy as social preferences that may influence generosity in this sample. From my reading, there is only one paragraph (on page 4) that focuses on "observed" signs of solidarity and anti-social behaviors, but there is a lack of citations to relevant literature (such as Mesurado et al. 2021; Dinić and Bodroža 2020; Buso et al. 2020), so the reader is asked to take the authors' word on this. More explanation, and nuance of how this may manifest, is needed. 7. The paper describes the study's objectives (3), but does not provide concrete and testable hypotheses that they have designed the study to test. If the study is exploratory (as I suspect it is), that is perfectly fine, but the authors should 1) state that the study is exploratory and 2) detail the potential outcomes for their objectives and what the outcomes would mean for generosity during the pandemic (i.e., that people were more or less generous during the lockdown).
8. The authors state: "We thus ask whether generosity changes differently across people depending on the true vs. perceived Covid-19-associated mortality" But, having read through the manuscript, it is not clear how they do this. Making the operationalization of these concepts and the subsequent hypothesis and meaning transparent would help readers feel guided through this part of the experiment.
9. The structure of the paper would be significantly improved if the authors implemented a more traditional introduction-method-results-discussion and conclusion format. The interpretation and implications of the results are currently presented in tandem with previous research in the introduction and, to put it plainly, this format makes it hard to follow the logic that motivated the current study. By interpreting the results in the introduction (before the reader has had a chance to read and evaluate the results for themselves; pages 5 -8), the reader just has to trust that they would interpret the results similarly. For example, statements like: "The decreased generosity detected in our study might partially explain these results.", "While our results are in line with the latter evidence, all these findings indicate that social behavior adapts following a complex pattern and that both short-term and long-term dynamics need to be considered separately.", "Last, as mentioned above, Campos-Mercade et al. (2021) report correlations between social preferences and health behaviors, highlighting the importance of our findings for the effectiveness of frequent public recommendations and policies appealing to human otherregarding concerns during the pandemic." imply that the reader already knows the results and can assess the accuracy of these claims for themselves, something that is not possible in an introduction before results are shown. The discussion of the results (pg 5 -8) is more important for a discussion section, though many of the ideas and descriptions need more explanation for readers to assess them easily.
10. Throughout the manuscript, the authors refer to one variable as "contagion" and "cases." It would be best to refer to the same variable by a single term, and "cases" is probably the most accurate (since the variable reports the number of cases in Spain for that day).
11. The methods section mentions that participants were incentivized to further recruit participants -how was this done?
12. As far as the method section describes, this study was co-opted for this purpose (i.e., it was originally planned for another purpose). If this is not the case, the writing needs to be clearer to describe how the authors made the study in response to the announced lockdowns. Currently, the impression is that students were already participating, and the purpose of the study changed once the lockdown was announced (which calls into question whether a sensitivity analysis or a priori power analysis is needed -It is currently also unclear which the authors present here).
13. When the authors talk about their balanced sample, it is a little unclear if they mean balance between the March 20-22 and March 23-25 groups or balanced in terms of generalizability to the overall Spanish population.
14. It is unclear what the experimental earnings are and how they were converted into lottery tickets (e.g., is 1 euro = 1 lottery ticket?; how much did people earn on average?).
15. There are many potential DVs mentioned in the text that are not fully described in the resultswhere are the results of the cognitive reflection, risk preferences, loss aversion, time preferences, stag hunt, and Big -5 variables? The manuscript says all other variables, but that doesn't give enough information.
16. It would be very helpful to discuss the overall regression analysis results (and type of regression used) in the text on page 12 instead of directing the readers to the table for the information.
17. The kinds of coefficients reported needs to be more explicit. Regression analysis gives both standardized and unstandardized coefficients, and there is nowhere in the text that specifies what coefficient the authors are interpreting & comparing across models (though, hopefully, it is the standardized coefficients).
18. Results, coefficients, standard errors, and p values jump between percentages and decimals. Please pick the format you intend to use for these variables and make it consistent throughout the manuscript.
19. Please give the coefficients/ effect sizes for the effects described -giving p-values does not give the reader enough information to assess the size of the effect beyond saying that the effect exists (which is not surprising given the large sample). I noticed this starting on page 14. 20. It is very odd to report results that are coming from another preprint (page 14, footnote 12), and I am not sure this inclusion buys the authors much in terms of explanations as it is not fully clear why this other analysis from the same data but in another paper is necessary. My reading of this part was that there wasn't a massive influence of day x age when controlling for day x expectations, but it is important enough to be in another paper, so it seems like the authors are misleading the reader as to somethings else regarding this analysis that could be important. Since I do not think this is the authors' intention, it might be best to add this as a footnote or completely omit it from the current manuscript.
21. It would be helpful to know the kind of coefficients for tables 1 & 2, and to specify that the numbers in parentheses mean SE. It is also unclear what "Province FE" refers to.
22. There were a lot of tests in this manuscript but no mention of corrections for multiple tests. It would be helpful for the authors to mention which of these effects survive correcting for multiple tests.
23. It is unclear why the authors begin referring to solidarity and envy as "SR-solidarity" and "SR-envy" as all of their data is self-report (even the donations). There are no objective measures in this study simply because the experiment was conducted online while people were stuck at home. In addition, the authors have some rationale in the introduction as to why they thought solidarity and envy would be important, but it is still not clear why these measures and not others were used. 24. The authors state " The moderation effect of age on giving is robust to controlling for selfreported solidarity and envy though." but it is not clear what analysis the authors are referring to as Table 1 suggests envy and solidarity were in separate models and outcome variables.
25. I believe that the authors mean that exposure to public information (e.g., deaths, cases, ICU patients) causes donations to decrease. Still, the wording "donations scale down" implies that the donations decrease in a scaleable form as more access/ exposure to information is included in the model. As that is not how table 2 presents the data, more clarity is needed here.

26.
It is unclear what the authors mean with "Shachat et al. (2020) perform a longer time horizon analysis in Wuhan, China and find long-term increases in prosociality after a decline in the immediate aftermath of the city lockdown. Our findings are consistent with such a pattern and, together, suggest that the behavioral adaptation process may follow complex dynamics." pg 20. The "behavioral adaptation process" aspect is not clear -do you mean changes in prosociality?
27. This section is also not clear (pg. 20) "The results would also have broader implications for the building of social resilience to future disasters, for which large-scale collective response is as important as for the Covid-19 pandemic. Such challenges are numerous (Boyd et al., 2018)." 28. By this point in the discussion, the effects of age are referred to as moderating effects -but this language was not used in the results section. It would be helpful to call the age effects similar things across all sections of the paper (for consistency from the reader's perspective, I had to go back and make sure the effect was a moderation effect instead of something else).
29. Toplak et al. is missing from the reference section.
30. I'm not sure if I missed it in my download, but I did not have access to the Appendix. I also was not able to access the link to the anonymous data file from the link provided.
While my critiques of the manuscript seem numerous, I would like to reassure the authors that this is only the case because I firmly believe there are many more positive aspects of the manuscript than things I can critique. My main concern primarily deals with the framing of the manuscript, which is why I have suggested a major revision.
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Decision letter (RSOS-210919.R1)
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Referee report: Exposure to the Covid-19 pandemic and generosity
I enjoyed a lot reading the paper! I think that the authors do a fantastic job at motivating and writing it. I also believe that understanding the effects of the pandemic is very relevant, and I appreciate the effort that the authors have put in trying to understand these effects on social preferences. I believe that this paper could make a great publication for this journal. However, I think that the paper would benefit from addressing a few issues.
Here are my main comments: 1) -Is the effect that the authors find a result of being exposed to the pandemic or to the lockdown? Drawing from both personal experience and previous literature, I suspect it is more likely to be the latter: When the experiment started, people were already in lockdown and very likely felt that they were exposed to the pandemic. After one week of being in lockdown, I am not convinced that seeing on TV that there are 500 deaths, rather than the 400 deaths that appeared yesterday, makes people feel "more exposed to the pandemic". Rather, people may be more sensitive to the fact that they have been closed at home, without the freedom to do what they like to do (meeting up with friends, playing football, or going hiking) for a long time. The authors may want to take a look at Layard et al. (2020), Andersson et al. (2021), and Giuntella et al. (2021) who discuss that the psychological costs of lockdowns can be substantial.
-Embracing the lockdown explanation would yield a much more consistent story with the rest of the literature. Most papers find that exposure to the pandemic fosters social preferences (Shachat et al. 2020;Cappelen et al. 2020). There are also two recent papers that I have reviewed that find that the pandemic increases cooperation to fight climate change (unfortunately, there are no working papers for those papers, but they should be out in a few weeks/months). However, it seems that lockdowns may damage social preferences in the short run (Buso et al. 2020;Shachat et al. 2020). Hence, the effect that the authors find would be very much in line with the literature if they instead interpret them as being due to having stayed 2 weeks (rather than 1) under lockdown and without freedom of movement.
-If the authors agree that, given their experience and the rest of the literature, it is likely that they are capturing lockdown effects, I would encourage them to slightly change the focus of the paper in that direction. If they do not agree, then I believe that the paper should discuss in detail this alternative explanation and why the authors think it is not a likely one.
-I would like to highlight that, regardless of the route that the authors decide to take, in my view the scientific value of the paper would remain intact.
2) The text often implies that the fact that deaths/cases/ICU cases correlate with generosity indicates that the effect on generosity comes from exposure to this information. However, if generosity decreases over time, and if these measures increase over time, the correlation is very likely to be there even if these measures have nothing to do with Appendix A generosity. So, personally, I do not think that this analysis brings much to our understanding of the mechanisms. I would tone down these discussions and potentially send the analysis to the appendix.
3) Given that all Spain went into lockdown, it seems weird to exclude 191 participants because they were not Andalusian. I understand the point that these may be unevenly distributed across time, but the econometric analysis should be able to deal with this by including region fixed effects.
4) I appreciate that the authors split the sample into two halves, one for the first and one for the second period. I think that this helps interpreting the results and generating easily interpretable figures. However, the effects of pandemic/lockdown exposure should in theory increase daily (rather than once mid-week), so including the "time" variable linearly would in my view make a more correct specification. I would provide these results, together with a figure showing the average donation made every day, either in the main text or in the appendix.
Minor comments: -At the end of page 12, why do the authors divide age in +/-29 years old? Is there some reason behind this cutoff? The wording could also be improved ("we accept a negative significant impact at 5%"). Similarly, in page 16 the authors use a cutoff of +/-24 years old. But in the rest of the paper the authors use +/-40. Since the analysis was not preregistered, I believe it is important to stick to one definition. -Proposal (feel free to disregard): I would give the correct number of participants in the abstract, rather than an approximation. -Proposal (feel free to disregard): The last sentence in the abstract does not read great. I am also not sure whether the information contained there is relevant enough. -Proposal (feel free to disregard): I would mention the shortcomings in the conclusion rather than in the introduction. -Proposal (feel free to disregard): The title could be more informative by replacing "and" for a verb. For example, "Exposure to the Covid-19 pandemic reduces generosity" or "Exposure to lockdowns reduces generosity" -Typos: -Second paragraph, second line: change "crisis" for "crises" -4 th page, second line: "in case of covid-19" for "in the case of covid-19" -8 th page, third line: "but this not prevented" for "but this did not prevent" Dear Reviewer, first of all, we would like to thank you for your positive assessment of our manuscript and for all the feedback you have provided. Your comments were very constructive and helped us to improve considerably the manuscript.
In what follows, we reply to your comments one by one. For a better readability of our reply, we preserve your comments in this document in italics and reply on them right below the corresponding points (starting with the word "REPLY:"). Please, note that, apart from the modifications due to your comments, there is quite a large number of changes made on request of Reviewer 2.
1) Is the effect that the authors find a result of being exposed to the pandemic or to the lockdown? Drawing from both personal experience and previous literature, I suspect it is more likely to be the latter: When the experiment started, people were already in lockdown and very likely felt that they were exposed to the pandemic. After one week of being in lockdown, I am not convinced that seeing on TV that there are 500 deaths, rather than the 400 deaths that appeared yesterday, makes people feel "more exposed to the pandemic". Rather, people may be more sensitive to the fact that they have been closed at home, without the freedom to do what they like to do (meeting up with friends, playing football, or going hiking) for a long time. The authors may want to take a look at Layard et al. (2020), Andersson et al. (2021), and Giuntella et al. (2021) who discuss that the psychological costs of lockdowns can be substantial. Embracing the lockdown explanation would yield a much more consistent story with the rest of the literature. Most papers find that exposure to the pandemic fosters social preferences (Shachat et al. 2020;Cappelen et al. 2020). There are also two recent papers that I have reviewed that find that the pandemic increases cooperation to fight climate change (unfortunately, there are no working papers for those papers, but they should be out in a few weeks/months). However, it seems that lockdowns may damage social preferences in the short run (Buso et al. 2020;Shachat et al. 2020). Hence, the effect that the authors find would be very much in line with the literature if they instead interpret them as being due to having stayed 2 weeks (rather than 1) under lockdown and without freedom of movement. If the authors agree that, given their experience and the rest of the literature, it is likely that they are capturing lockdown effects, I would encourage them to slightly change the focus of the paper in that direction. If they do not agree, then I believe that the paper should discuss in detail this alternative explanation and why the authors think it is not a likely one. -I would like to highlight that, regardless of the route that the authors decide to take, in my view the scientific value of the paper would remain intact.
REPLY: We do agree. The argument that the documented effects may be influenced by the home confinement is obviously valid. However, our data do not allow us to conclude whether the observed effects are due to the pandemic threat, the home confinement, or both. Although our analysis of moderators suggests that the health-related (perceived) threat does influence the change in generosity (note that lockdown restrictions affected everyone similarly but the perceived health-related threat focused on the elder), we cannot discard that the lockdown itself also has an impact. It might be that the lockdown affects especially older individuals, but we see this explanation somewhat less reasonable for the age moderation effect than the threat-related explanation. In fact, the literature points to a stronger negative effect of lockdowns among the youth (Czeisler et al., 2020;Giuntella et al., 2021), which would suggest a moderation effect of age in the opposite direction as we find. In addition, the health-related information data provide a slightly better fit to the data than a linear time regressor (see reply to comments #2 and #4), which also talks against the interpretation of the lockdown as the main driver. That said, we opted for an intermediate discourse, in which we admit this possibility and acknowledge that we cannot fully separate the two. This approach can be visible in the new title (we included the word "environment" to make clear that we refer to the pandemic situation, with all its numerous associated factors), the abstract, and throughout the whole Introduction section. In addition, in Discussion and Conclusion, we follow your suggestion and discuss this issue in detail and in relation to the literature.
However, we now review the existing literature in more detail both in the Introduction and the Discussion and Conclusion sections and conclude that the evidence regarding the effect of the Covid-19 pandemic is rather mixed even within studies. For example, Shahat et al. observe an initial decrease and later increase in generosity. Cappelen et al. make the pandemic more salient through priming, showing that it increases solidarity but also the acceptance of inequality due to luck. However, all their subjects are exposed to the Covid-19 pandemic. Hence, we prefer to be more cautious in the manuscript without making any general inferences regarding this point (but still recognizing the possibility that you raise in this comment).
We hope that you like the way we addressed this comment.
2) The text often implies that the fact that deaths/cases/ICU cases correlate with generosity indicates that the effect on generosity comes from exposure to this information. However, if generosity decreases over time, and if these measures increase over time, the correlation is very likely to be there even if these measures have nothing to do with generosity. So, personally, I do not think that this analysis brings much to our understanding of the mechanisms. I would tone down these discussions and potentially send the analysis to the appendix.
REPLY: The comparison of the models with time as a continuous variable (Table A6; built to address your comment #4) and the public data ( Table 2 in the original version) suggests that the employment of the public figures slightly improves the model performance. This suggests that public information might be a fundamental factor, but the results are by no means conclusive in this respect. Therefore, following your suggestion, we reduced considerably the corresponding discussion in the Results section and moved most of it-including the original Table 2-into the Appendix A4 (the old Table 2 became Table A4 in the new version). In addition, we discuss this issue in several parts of the current version of the paper.
3) Given that all Spain went into lockdown, it seems weird to exclude 191 participants because they were not Andalusian. I understand the point that these may be unevenly distributed across time, but the econometric analysis should be able to deal with this by including region fixed effects.
REPLY: Since the experiment from the very beginning targeted Andalusian subjects, we had little control over the participation outside of the region. We do not know the reasons why people from outside the target region participated but these might be spurious. As a result, the non-Andalusian subjects are unevenly distributed both across time and space. In addition, the non-Andalusian participants differ from the Andalusian ones in some aspects: e.g. they are more educated (difference=-0.59, p<0.001) and younger (difference= -2.94, p<0.001). Note also that, given the low numbers in some of the regions (see below), the region fixed effects may be blurring part of the effect of the remaining variables (in particular, exposure). We therefore maintain the models with Andalusian subjects only as the benchmark analysis.

Region
Freq REPLY: Similarly to your comment #3, since the observations are unequally distributed across the six days under study (see Table A1), we opted for being more conservative and employ the time dummy. This analysis is kept in Table 1.
However, upon your request, Table A6 in the Appendix now reproduces our regressions using the proposed linear relationship as a robustness check. One again, the results are qualitatively unaffected with one exception: under this model specification, the day×age interaction is still negative but no longer significant. However, the Wald test employed on the model estimates still detects a negative significant relationship for people aged 30 or more while the effect for people aged 29 or less is non-significant, using p=0.05 as a threshold (in this respect, see also our reply to your first Minor Comment below). In addition, as requested, Figure A9 plots the average donations day by day, and the estimated linear relationship, disaggregated by age.
Minor comments: -At the end of page 12, why do the authors divide age in +/-29 years old? Is there some reason behind this cutoff? The wording could also be improved ("we accept a negative significant impact at 5%"). Similarly, in page 16 the authors use a cutoff of +/-24 years old. But in the rest of the paper the authors use +/-40. Since the analysis was not pre-registered, I believe it is important to stick to one definition.
REPLY: We realize that we might have not explained ourselves well: the main figures fix one age exogenously (40 years) and look at the below/above 40 difference for visual clarity.
However, for the regression analysis we use age as a continuous variable and since our study is explanatory (and this is clearly expressed in several parts of the paper), as is standard when the moderator is continuous, we also ask: "Above which threshold age is the effect significant in the data?" This "endogenous" threshold age, obtained through Wald tests on the coefficients evaluated at the different ages, is then reported in the text. This explains why the number differs depending on the model or type of analysis. To make this distinction clear for future readerships, we explain this better in the manuscript. Please see the Results section. Thank you for pointing our attention to the confusion this might generate.
Moreover, note that such an endogenously obtained age is very similar across models with the same dependent variable: it is 29 or 30 in all the models in which generosity is the dependent variable. The age of 24 shows up only in the regressions that control for self-reported solidarity/envy. We therefore find it useful to maintain this exercise in the analysis.
-Proposal (feel free to disregard): I would give the correct number of participants in the abstract, rather than an approximation.
-Proposal (feel free to disregard): The last sentence in the abstract does not read great. I am also not sure whether the information contained there is relevant enough.
-Proposal (feel free to disregard): I would mention the shortcomings in the conclusion rather than in the introduction.
-Proposal (feel free to disregard): The title could be more informative by replacing "and" for a verb. For example, "Exposure to the Covid-19 pandemic reduces generosity" or "Exposure to lockdowns reduces generosity" REPLY: All changed as suggested. In the abstract, we report the exact number of subjects and removed the last sentence. In addition, we moved the discussion of shortcomings into the Discussion and Conclusion section and (due to your comment #1) changed the title to "Exposure to the Covid-19 pandemic environment and generosity." We included the word "environment" to reflect that with the pandemic we refer to all the conditions of the pandemic (including the home confinement but also other phenomena). We also prefer not to include "reduces" in the title because the discussion of the literature clearly argues in favor of a more complex pattern than just "reduces" (see our reply to your comment #1 and the Discussion and Conclusion section in the manuscript). Given this, we prefer not to give such a strong message in the title. We hope you like it.
Typos: -Second paragraph, second line: change "crisis" for "crises" -4th page, second line: "in case of covid-19" for "in the case of covid-19" -8th page, third line: "but this not prevented" for "but this did not prevent" REPLY: All fixed. Thank you.
Reply to Reviewer 2: Dear Jessica, thank you very much for your positive assessment of our work and for such a detailed reading of and comments on our paper. There is no doubt that addressing your comments has considerably improved our paper. Thank you very much for that.
In what follows, we reply to all your comments one by one. For a clearer exposition, we leave your comments in this reply in italics and reply to each of them right below the corresponding comment (each time starting with the word "REPLY:"). Please, note that, apart from the modifications due to your comments, there are numerous other changes made on request on Reviewer 1.
1. The manuscript has minor spelling/ grammatical errors (e.g., use of different tenses in the same paragraph, plural vs. singular nouns and verbs). While this is not a significant issue (as these are issues I also commonly run into in my writing), I found myself distracted by these instances and unable to focus on the authors' argument. I feel that the authors would be able to address these instances with another readthrough of their manuscript.
REPLY: A native speaker proofread the manuscript. We hope that there are no remaining errors in the text.
2. In the abstract, it would help to have a little more precision and clarity. For example, why not use the exact number of participants instead of a rounded approximation? Why not separate the results to state their importance clearly? Why not list that solidarity and empathy are the "social preferences" that are studied? As is, it feels like the reader needs to have read the manuscript in its entirety to fully understand and appreciate the work the authors present in the manuscript.
REPLY: We incorporated all your suggestions (as well as the suggestions of Reviewer 1). We report the exact number of subjects and (in response to Reviewer 1) we removed the mentioned sentence referring to social preferences and the result regarding the public information. As a consequence of the latter, the results-we hope-are separated more clearly: we present in one phrase the main result (donations decrease with time, particularly among older participants) and in another phase we summarize all the suggested mechanisms behind the documented effect. We hope that you like the new version of the abstract and consider it self-explanatory.