The Effect of Country Economic Institutions and Cultural Values on Government Policy and Societal Compliance in the Covid-19 Pandemic

Abstract

Using data from 88 countries, we test hypotheses linking a country’s economic freedom and cultural values with the propensity and timing of decisions to impose stringent policies to combat the spread of Covid-19, as well as society’s compliance with those restrictive measures. Our analysis supports hypotheses that a country’s economic freedom and cultural dimensions of individualism and masculinity predict early implementation of stringent policies. After accounting for endogeneity, we find that individualism also helps explain residents’ compliance with stringent measures. These findings illustrate how institutions and cultural values influence government policies and societal compliance.

Keywords

citizen compliance Covid-19 cultural values economic freedom government policies

When Covid-19 hit, national leaders faced agonizing choices, given that policy actions to protect citizens’ physical health actually compromised their economic health. Governments issued varying guidance and mandates for their populations, ranging from informal appeals to socially distance to strict closures and lockdown measures. There has been widespread debate over governments’ choices in balancing public health and economic objectives in their emergency responses, yet it remains unclear what country-level factors predict both policy decisions and societies’ responses to those restrictive measures. Nevertheless, the global effect of Covid-19 restrictions was enormous, with the number of hours worked worldwide declining to the tune of 255 million full-time job equivalents (International Labour Organization [ILO], 2021).

Research has investigated how political institutions affected the speed and aggressiveness of countries’ pandemic responses (D. Chen et al., 2021; Frey et al., 2020). However, we contend that policy decisions and societal compliance will reflect not only countries’ formal political environments, but also a broader set of factors that shape worldviews, including informal institutions and cultural values. Thus, we use the pandemic to study how, in times of crisis, countries’ economic institutions and cultural values influence policy responses, as well as societal compliance with the resulting measures.

Theory and Hypothesis Development

Institutions, Values, and Policy Responses

Countries manifest unique combinations of institutions—encompassing codified regulations, informal norms, and socially shared expectations (Helmke & Levitsky, 2004). Institutions influence how residents make sense of their world, and how they assess the appropriateness and legitimacy of actions (Jepperson, 1991). By conforming to societal expectations, entities increase their own legitimacy and thus garner rewards such as improved reputation, resources, and survival (Zucker, 1987). Indeed, government leaders often undertake actions conducive to preserving political legitimacy, which relies on political and social trust, ensuring citizens’ satisfaction with officials’ intentions and performance (O’Sullivan et al., 2014; Rothstein, 2009), and maintaining the perception that decisions conform to both the rule of law and society’s normative beliefs (Beetham, 2013). When citizens view power as properly acquired, held, and exercised, they are more likely to accept and obey leaders’ mandates (Beetham, 2013; O’Sullivan et al., 2014).

During crises, government leaders typically hold discretion to pursue emergency measures that sidestep formal institutions (Greene, 2020; Gross, 2020; Kipfer & Mohamud, 2021). For example, in 2020–2021, at least 112 countries announced states of emergency justifying limitations on personal freedoms (International Center for Non Profit Law [ICNPL], 2022). Thus, countries’ formal regulations and legal constraints on the executive cannot directly explain varying responses during the pandemic. Nevertheless, we expect governments’ responses to be consistent with their country’s established institutions and shared normative beliefs and values for two reasons. First, leaders, themselves, will have internalized domestic norms and beliefs, often unconsciously through deeply internalized mental representations (Peterson & Smith, 2008). Second, leaders will purposefully abide by their country’s institutions and cultural values to maintain political legitimacy and increase society’s likelihood of compliance.

Economic Institutions

Economic freedom (Miller et al., 2020) encompasses the formal laws, practices, and institutional structures that constrain government intervention into economic life. Most emergency restrictions that leaders contemplated to address the pandemic’s public health threat infringed—sometimes extensively—upon this economic freedom, placing citizens’ economic well-being at risk.

Countries’ economic institutions tend to correspond broadly with their society’s norms and values (Holmes et al., 2013; Weber & McManus Warnell, 2020). While governments could circumvent regulatory constraints via state-of-emergency pronouncements, we argue that leaders will continue to consider their country’s economic freedom-related traditions when formulating policies, both because their own values likely align with these norms and because conformity with national institutions will help leaders maintain political legitimacy.

Hypothesis 1 (H1): A country’s level of economic freedom will be negatively associated with the timing and probability of a stringent policy response.

Cultural Values

Culture creates a lens through which individuals evaluate external events, make judgments, and formulate responses (Peterson & Smith, 2008). As culture establishes a shared social viewpoint, we expect it to influence both the policies leaders choose to implement and society’s response to imposed restrictions.

Although recent studies have explored how some cultural dimensions influenced Covid-19 growth rates (Dheer et al., 2021; Gokmen et al., 2021), we do not focus directly on case counts because virus spread varied not only due to government policies but also because of other factors such as pre-existing norms to wear masks, lifestyle differences, and even governments’ accuracy in tracking and reporting cases. Some scholarly studies have predicted relationships between culture and government policies (D. Chen et al., 2021; Nelson, 2021) with inconsistent empirical results, and others have predicted societal compliance (C. Chen et al., 2021; Frey et al., 2020; Lu et al., 2021), but without accounting for the endogeneity arising because societal norms influenced both government policy and societal responses. In this article, we assess the relationship between culture, policy stringency, and societal compliance using a large sample of countries and accounting for endogeneity in the hypothesized relationships.

Individualist societies emphasize independence and self-interest (Hofstede, 2001), whereas collectivist societies emphasize interdependence and prioritization of the collective (Markus & Kitayama, 1991). As emergency measures to slow Covid-19’s spread required society-level collective action, this dimension has received the most attention, though with mixed empirical results—some finding flatter case growth in individualist countries (Messner, 2020) and others finding a positive relationship between individualism and case growth (Gokmen et al., 2021). In terms of policy outcomes, some have found a non-significant relationship between individualism and policy aggressiveness (Nelson, 2021), whereas others have found collectivist countries to have enacted mask mandates, lockdowns, and other policies more quickly (D. Chen et al., 2021; Melton & Sinclair, 2021). Finally, Dheer and colleagues (2021) found faster case growth in more individualist countries and a stronger attenuating effect on the relationship between government stringency and case rates in collectivist cultures.

Given our expectation that leaders have internalized the values of their society, and that they pursue political legitimacy, we expect countries to enact policies that conform to societal norms and values. Thus, we hypothesize that a society’s individualist orientation will deter political leaders from imposing restrictive policies as people in individualist cultures disdain regulations that impede the pursuit of self-interest (Holmes et al., 2013). We also expect that even after accounting for leaders’ tendencies to formulate policies consistent with domestic norms and values, more individualist countries will exhibit lower compliance because residents will prioritize individual interests over collective interests, even if it means circumventing government mandates.

Hypothesis 2 (H2): Higher individualism will be negatively associated with the probability and timing of a stringent policy response.

Hypothesis 3 (H3): Higher individualism will be negatively associated with societal compliance.

Uncertainty avoidance reflects society’s comfort with ambiguous or uncertain situations (Hofstede, 2001) and is associated with a societal preference for unambiguous rules and directive leadership (Taras et al., 2010). In research on infection control, uncertainty avoidance was associated with greater antibiotic use, possibly because prescribing antibiotics offers reassurance and certainty (Borg, 2014). In research on Covid-19, Dheer and colleagues (2021) found uncertainty avoidance to be positively related to case growth, but Gokmen and colleagues (2021) found no direct effect. Neither study considered the direct effect of uncertainty avoidance on policy stringency or societal compliance.

We expect uncertainty avoidance to associate with faster and more stringent policies because the crisis will likely inflict greater stress on populations of uncertainty-avoiding cultures, and this heightened stress may be alleviated via firm rules and guidelines (Taras et al., 2010). Such policies to reduce ambiguity and provide certainty will reflect leaders’ own internalization of uncertainty avoidance values and also enhance their political legitimacy as they earn greater trust of their citizens. Likewise, as people in uncertainty-avoiding cultures tend to value rules and order, we expect them to be more likely to observe such policies, when imposed.

Hypothesis 4 (H4): Higher uncertainty avoidance will be positively associated with the probability and timing of a stringent policy response.

Hypothesis 5 (H5): Higher uncertainty avoidance will be positively associated with societal compliance.

Masculinity reflects two interrelated concepts: gender egalitarianism and the notion of male assertiveness versus female nurturance (Hofstede, 2001: 284). Masculine societies tend to prefer assertiveness, achievement, and material reward (Taras et al., 2010), whereas feminine societies emphasize cooperation, nurture, quality of life and, we would expect, a preference for caring for the weak and sick. Accordingly, Dheer and colleagues (2021) proposed that masculine societies would have a higher Covid-19 case growth though, surprisingly, found the opposite relationship.

Given the possible differing relationships between assertiveness and nurturance values and policy decisions in a scenario such as this, we propose contrasting hypotheses. On one hand, feminine societies may be prone to enact stringent restrictions as a way of protecting weaker members of society. On the other hand, a hallmark of masculine societies is their preference toward assertive action and directive leadership. Thus, leaders in masculine societies may view timely stringent policies as the more socially acceptable response.

Regarding compliance, we expect people in more masculine societies to emphasize personal achievement (which would be compromised by restrictive measures) and people in more feminine societies to accept governments’ guidelines to prioritize others’ well-being by complying with stay-at-home initiatives.

Hypothesis 6a (H6a): Higher masculinity will be negatively associated with the probability and timing of a stringent policy response.

Hypothesis 6b (H6b): Higher masculinity will be positively associated with the probability and timing of a stringent policy response.

Hypothesis 7 (H7): Higher masculinity will be negatively associated with societal compliance.

Power distance reflects how a society views inequality (Hofstede, 2001). In high power distance cultures, individuals accept differences in power, with lower-ranked individuals typically behaving submissively toward those in power. In low power distance cultures, people with power are more likely to share decision-making with subordinates, who also expect this (Brockner et al., 2001).

Messner (2020), Gokmen and colleagues (2021), and Dheer and colleagues (2021) found a negative relationship between power distance and case growth. Although Chen and colleagues (D. Chen et al., 2021) found no relationship between power distance and speed of Covid-19 policy implementation, Dheer and colleagues (2021) found that early policy stringency moderated case growth more in high power distance cultures.

We argue that in societies with high power distance, leaders will innately favor quick autocratic decisions in times of crisis, and that their citizens will view such directives positively, which should reinforce political legitimacy. We also expect greater compliance in higher power distance societies, given that individuals generally tacitly cede authority to those in power.

Hypothesis 8 (H8): Higher power distance will be positively associated with the probability and timing of a stringent policy response.

Hypothesis 9 (H9): Higher power distance will be positively associated with societal compliance.

Method

Data Sources

Dependent Variables

To operationalize governments’ imposition of stringent policies, we used data compiled by Our World in Data, OWID (Roser et al., 2020; Roser & Ortiz-Ospina, 2020). This research group distilled policies to nine categories using ordinal scales to classify measures such as closures, public event cancelations, and stay-at-home orders (Hale et al., 2020). For example, for stay-at-home initiatives, the group tracked whether each country imposed stay-at-home recommendations (Category 1); stay-at-home orders, allowing essential activities (Category 2); more stringent stay-at-home orders with few exceptions (Category 3); or no stay-at-home recommendations/requirements. The resulting daily stringency score (combining all nine categories) adjusted when policies applied only within some regions of a country.

Each country’s maximum stringency level was calculated based on the highest daily score implemented from January 13, 2020, to June 11, 2020 (150 days). Countries’ maximum scores averaged 83.21 during this period. We calculated the number of days that spanned from the third confirmed case until each country’s policies hit the global mean to measure probability/timing of stringent response. The variable ever hit stringent response took the value of 0 if a country never hit the threshold level and 1 if it did (the “status” variable).

To measure compliance with stay-at-home order, we used Google Mobility Reports (Google, 2021), which employed anonymized mobile phone data to measure how residents’ movement patterns changed. Compliance reflected the percentage decrease in travel to three categories of locations—retail and recreation (excluding groceries/pharmacies), transit stations, and workplaces—on the seventh day after a Category 2 stay-at-home order. Values were reversed so that higher values reflect greater compliance. Countries that rescinded their orders before that were removed, and when announcements fell on a weekend, we used the change-from-baseline starting Monday. The first stage of the selection model used the Roser and Ortiz-Ospina (2020) stay-at-home orders, with ever a stay-at-home order taking 1 if the country announced a Category 2 order and 0 if it did not (other categories were too small for analysis).

Independent Variables

Economic freedom was measured using country ratings from Heritage Foundation (Miller et al., 2020). Individualism, power distance, masculinity/femininity, and uncertainty avoidance used Hofstede’s country-level scores (Hofstede Insights, 2020).

Controls

To define the boundaries of our model and address potential endogeneity from omitted variables, we included several controls. Given that the virus traveled in humans and that travel patterns reflect economic, cultural, and language ties (Ghemawat & Reiche, 2016), along with the fact that countries with later virus arrival benefited from viewing earlier countries’ approaches, we controlled for virus arrival timing (days from the first case reported outside of China on January 13, 2020, until arrival in each country plus one,¹ logged) and case increase rate (days until the 10th announced case). Virus arrival and growth could be related to the country’s population size, which can likewise affect officials’ capacity for action (Dheer et al., 2021) and tendency toward country-wide restrictions. Thus, we controlled for the country’s logged population size (The World Bank, 2020b).

Countries’ cultural values have been associated with regulatory quality (Porcher, 2021) and investments in national health (Hofstede, 1995), which have clear potential to affect Covid-19 policies and societal compliance. Thus, we controlled for regulatory quality (Kauffman & Kraay, 2020) and public health expenditures as a percentage of GDP (World Health Organization [WHO], 2019).

Scholars have tied countries’ political institutions to their cultures (Porcher, 2021), and federalism is positively correlated with cultural variables such as masculinity. Hence, we controlled for federalist countries (Forum of Federations, 2021) because those countries were less likely to meet the mean stringency threshold given that the measure adjusts when policies do not apply nationwide.

In addition, scholarship has linked countries’ per capita GDP with culture (Tang & Koveos, 2008), and income level should associate with greater societal compliance because residents of wealthier countries can better withstand restrictions. Therefore, we control for logged PPP per capita GDP (The World Bank, 2020a).

Modeling

To test policy timing and stringency hypotheses, we used a Cox proportional hazard model, which is a survival model that accounts for the likelihood that a country will hit the threshold level of policy stringency, and the time span before the predicted event occurs. The hazard model was estimated using the specification, h_i(t|X_i) = h₀(t)exp(X_i β), where the hazard function for the ith country is conditional on covariates X. The term h₀(t) reflects the hazard when all predictors (X_i) are equal to zero (h_i(t|X_i) = 0). Covariates X_i included both the hypothesized variables of interest and control variables, and the model specified robust standard errors. To meet the model’s proportional hazard assumption, we employed a Cox with time-dependent covariates model, which includes the virus arrival covariate along with its interaction term against time.

To test societal compliance hypotheses, we used a Heckman selection model with robust errors to predict the compliance of a country’s population with an announced stay-at-home order, recognizing the presence of a clear endogeneity issue. The first stage included the age of the president/prime minister based on the premise that this personal characteristic influenced leaders’ choices to impose a stay-at-home order, but not societal compliance.

Results

Table 1 summarizes descriptive statistics and correlations. Table 2 displays results of our main analysis predicting the probability and timing of stringent policy implementation.² A positive, significant coefficient indicates increased hazard for implementing stringent policies (the country hit the threshold and did so faster). A hazard ratio of 1.0 indicates that the variable does not affect the policy implementation while lower than 1.0 indicates lesser hazard. As seen in Column 2, virus arrival timing was positive and significant (p = .016), and its interaction with time was negative and marginally significant (p = .058). The case increase rate was also significant (p = .000). Federalist countries were less likely to hit the threshold (p = .001), and regulatory quality positively predicted policy stringency (p = .046). Economic freedom had a significant and negative coefficient (p = .004) with the hazard of implementing stringent policies, providing support for H1. H2, which predicted that individualism would associate negatively with the hazard of stringent policies, was also supported (p = .010). Masculinity emerged as positive and significant (p = .020), providing support for H6b. Hypotheses on uncertainty avoidance (H4) and power distance (H8) were not supported.

Table 1

Correlations.

Variables		M (SD)	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)
(1)	Virus arrival (log)	3.61 (0.73)
(2)	Case increase rate	11.91 (10.38)	−.47**
(3)	Population size (log)	16.73 (1.47)	−.35***	.30**
(4)	Per capita GDP (log)	4.31 (0.45)	−.36**	−.03	−.34***
(5)	Federalism	0.20 (0.41)	−.20^†	.17	.47***	.06
(6)	Regulatory quality	0.45 (0.91)	−.34***	−.01	−.36	.83***	.04
(7)	Health expenditure/GDP (log)	0.82 (0.18)	−.08	−.09	−.18^†	.32**	.10	.46***
(8)	Economic freedom	66.09 (9.53)	−.34***	−.01	−.36***	.78***	.01	.91***	.26*
(9)	Masculinity	46.71 (18.64)	−.10	−.10	.28**	.03	.31**	.03	.00	.04
(10)	Individualism	39.39 (22.77)	−.26*	.16	−.03	.58***	.28**	.69***	.52***	.55***	.15
(11)	Power distance	63.84 (21.64)	.12	.06	.16	−.42***	−.14	−.60***	−.53***	−.48***	.04	−.70***
(12)	Uncertainty avoidance	67.89 (20.97)	.17	−.23*	−.09	.11	−.08	−.12	.03	−.14	.01	−.27**	.27**

Note. N = 88; GDP = gross domestic product.

†

p ≤ .10. *p ≤ .05. **p ≤ .01. *** p ≤ .001 on two-tailed test.

Table 2.

Cox Proportional Hazard Model Predicting Early/Stringent Response.

Variables	(1)	(2)
Virus arrival	1.97* (0.88) [7.17]	2.34* (0.98) [10.36]
Case increase rate	0.07*** (0.02) [1.07]	0.10*** (0.02) [1.11]
Population size (log)	0.15 (0.16) [1.16]	0.20 (0.18) [1.22]
Per capita GDP (log)	0.77 (0.64) [2.16]	0.77 (0.89) [2.15]
Federalism	−1.17* (0.47) [0.31]	−1.48*** (0.46) [0.23]
Regulatory quality	−0.55^† (0.32) [0.58]	1.19* (0.60) [3.27]
Health expenditures per GDP (log)	−1.17 (0.96) [0.31]	−1.72 (1.11) [0.18]
Economic freedom		−0.14** (0.05) [0.87]
Individualism		−0.03** (0.01) [0.97]
Uncertainty avoidance		0.01 (0.01) [1.01]
Masculinity		0.02* (0.01) [1.02]
Power distance		0.00 (0.01) [1.00]
Virus Arrival × Time	−0.03* (0.02) [0.97]	−0.04^† (0.02) [0.97]
Chi-square	40.82***	52.19***
Change of chi-square from prior block		18.30* (5)

Note. β (SE) [Hazard Ratio], N = 88. GDP = gross domestic product.

†

p ≤ .10. *p ≤ .05. **p ≤ .01. ***p ≤ .001 on two-tailed test.

Table 3, Column 1 presents the Heckman analysis. The selection variable in Stage 1 was significant (p = .000). Virus arrival date was significant (p = .011) but case increase rate was not. Logged per capita GDP was positive and significant (p = .017) while other controls were insignificant. Supporting H3, individualism emerged as negative and significant (p = .034), indicating that in countries with higher levels of individualism, the population was less likely to comply with stay-at-home orders. However, masculinity, power distance, and uncertainty avoidance did not show significance in the predicted directions.

Table 3.

Heckman Model Predicting Societal Conformity With Stay-At-Home Order.

Variables	(1)	(2)
Virus arrival (log)	20.97* (8.23)	20.48** (6.99)
Case increase rate	0.13 (0.36)	0.16 (0.36)
Population size (log)	1.84 (2.44)	1.67 (2.36)
Per capita GDP (log)	26.75* (11.17)	26.01* (10.58)
Federalism	4.75 (6.88)	5.28 (6.40)
Regulatory quality	12.23 (8.48)	14.68^† (8.21)
Health expenditures/GDP (log)	11.64 (7.88)	9.90 (7.58)
Economic freedom	−0.87 (0.66)	−1.70** (0.66)
Individualism	−0.36* (0.17)	−1.72* (0.71)
Uncertainty avoidance	−0.22^† (0.12)	−0.21^† (0.12)
Masculinity	0.02 (0.16)	0.02 (0.15)
Power distance	0.09 (0.15)	0.16 (0.14)
Economic Freedom × Individualism		0.02* (0.01)
Constant	−118.40 (97.65)	−58.26 (81.94)
Lambda (inverse mills)	1.03 (7.21)	−1.70 (6.03)
Wald chi-square (p)	21.94*	27.71**

Note. β (SE). N (Selection = 84, final model = 60). GDP = gross domestic product.

†

p < .10. *p < .05. **p < .01.***p < .001 on two-tailed test.

As both economic freedom and individualism emphasize individual self-interest, we subsequently considered a model that included their interaction (p = .035), as shown in Table 3, Column 2, and displayed in the margins plot in Figure 1. In countries with minimum economic freedom, conformity with the stay-at-home order varied significantly across more and less individualist cultures, but in countries with high economic freedom, differences did not arise based on individualism.

Figure 1.

Predictive Margins.

In a series of supplemental analyses, we assessed the robustness of our culture hypotheses using data from the Global Leadership and Organizational Behavior Effectiveness (GLOBE) studies (House et al., 2004) that offer newer country ratings on constructs reflecting the values measure of in-group collectivism, uncertainty avoidance, power distance, and assertiveness. Data availability was sparser for this analysis, with sample size declining to 51 countries. GLOBE’s uncertainty avoidance measure was collinear with several variables; thus, we report results based on a model without the variable (conclusions remain the same when including uncertainty avoidance). Economic freedom remained negative and significant (β = −0.14, p = .032), and in-group collectivism was positive and significant (β = 1.67; p = .006); both of these are consistent with findings using Hofstede’s measures. The assertiveness variable did not show significance. The GLOBE power distance measure emerged as positive and significant (β = 1.23; p = .017), which is consistent with our original H8 prediction.

We performed robustness tests adding alternative control variables, using a different measure of the dependent variable, and considering sensitivity to omitted confounding variables. Additional variables included population density (replacing logged population; The World Bank, 2020b); percentage of the country’s population over age 65 (The World Bank, 2020b); latitude (Gapminder, 2021); income inequality (averaging 2014-2019 Gini Index, 2020); and logged public health expenditure per capita (WHO, 2019, replacing public health expenditure variable). Economic freedom, individualism, and masculinity remained significant (p < .05) for all in the Cox model, and individualism remained significant at either p < .10 or p < .05 in the Heckman model.

The regulatory quality control variable had a relatively high variance inflation factor (VIF) in the main model. Hence, we ran a check replacing it with Freedom House’s (2020) global freedom score where all VIFs fell below 5. In the Cox model, economic freedom, individualism, and masculinity all retained their signs and significance at p < .05. In the Heckman model, the p-value of individualism edged down to p = .074. In an analysis including China in the hazard model, all variables retained their sign and significance at p < .05. China implemented a Category 3 lockdown; thus, it was not suitable for the model predicting compliance.

We assessed the potential impact of any omitted confounding variables (Linden et al., 2019; Oster, 2019) and found that an unmeasured confounding variable would need to be associated with both treatment and outcome variables with a strength greater than 100% of measured variables to change conclusions in the Cox model and about 98% of the strength of the individualism variable to change conclusions in the Heckman model.

Discussion

Using the Covid-19 crisis as an exogenous event in which countries were facing the same, intense threat, we investigated whether countries’ economic freedom and cultural values affected leaders’ implementation of stringent emergency measures, as well as societal compliance with those policies. Our empirical results lead to three main conclusions. First, when faced with a crisis in which government leaders faced fundamental trade-offs between economic liberty and public health goals, their countries’ norms regarding economic freedom held significant sway in influencing policy stringency. Although leaders held wide latitude to sidestep formal constraints on their actions, our empirical results show that economic freedom was associated with a lower hazard of implementing stringent policies, and this finding persisted even with diverse robustness checks. We conclude that the informal, socially shared norms supporting formal institutions continued to guide leaders’ decisions even when the formal institutions were not subject to enforcement.

Second, individualism predicted both governments’ hazards of implementing strict policies and society’s compliance with those measures, highlighting the influence of this fundamental cultural value on both policy choices and societal behavior. Individualism associated negatively (and in-group collectivism, positively) with the propensity and timing of stringent measures. Moreover, even after accounting for non-randomness in stay-at-home orders, individualist values associated negatively with societal compliance. Furthermore, among countries with weaker economic freedom, collectivist societies demonstrated significantly higher compliance. Conversely, when either a country’s norms supported strong economic freedom or its national cultural values were more individualist, there was less societal compliance with policies that place collective, public health objectives above individual-level objectives.

Third, masculinity predicted governments’ implementation of stringent policies. The multidimensional masculinity construct suggests various avenues by which culture may influence policy decisions given that an assertive response (a masculine characteristic) was intended to achieve a collective public health benefit (a feminine objective). In addition, Hofstede’s empirical measure encompasses not only preferences for assertiveness and nurture but also societal diversity in the roles of men and women. The popular press has reported that countries with women leaders seemed to fare better in Covid-19 outcomes, but also noted that this success perhaps stemmed from their decisive action (Wittenberg-Cox, 2020). Our empirical findings similarly align best with the notion that in masculine societies, leaders acted decisively by implementing stringent policies.

Contrary to expectations, uncertainty avoidance did not significantly predict policy stringency. This may be because members of high uncertainty avoidance cultures prefer clear but not necessarily stringent rules—especially when such rules increase economic uncertainty. Finally, Hofstede’s power distance measure did not predict government policy stringency, though the GLOBE power distance measure was significant in the hypothesized direction. This result should be interpreted cautiously given the smaller sample size.

In conclusion, during times of crisis, even when leaders can bypass the constraints imposed by formal institutions, both national leaders and the population as a whole tend to be guided by the traditions and normative beliefs underlying societal institutions and cultural values. This holds important implications for managers trying to anticipate a government’s likely policy response to crises by considering their country’s long-standing institutions and values.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Carolina Gomez

Notes

Author Biographies

Carolina Gomez (PhD, University of North Carolina at Chapel Hill) is a professor of management at Florida International University. Her research interests focus on cross-cultural issues and management as well as national institutional environments. Her articles have appeared in journals such as Academy of Management Journal, International Journal of Human Resource Management, Journal of Management Studies, Journal of World Business, and Strategic Management Journal.

Jennifer Spencer (PhD, University of Minnesota) is a professor of International Business and International Affairs at George Washington University. Her research focuses on how firms’ embeddedness in national institutional environments affects their strategies and performance, including issues related to new product innovation, entrepreneurship, and corruption. Her articles have appeared in journals such as Academy of Management Journal, Academy of Management Review, Journal of International Business Studies, Organization Science, and Strategic Management Journal.

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