Appendix A

This section presents the statistics on respondents’ satisfaction levels for each public policy, including the healthcare system, the universal old-age allowance system, the disabled allowance system, the land transportation system, the water transportation system, the air transportation system, the disaster early warning system, and the emergency assistance system. Respondents rated their satisfaction levels as Strongly Dissatisfied (SD), Dissatisfied (D), Satisfied (S), and Strongly Satisfied (SS). The “Not Available” (NA) category represents respondents who indicated they had never heard of or participated in the policy (Missing observations (NA) are coded as 5). The table includes the frequency of respondents selecting each satisfaction level, the corresponding percentage for each category, and the cumulative percentage.

Fig. 1

Satisfaction level with public health policies

Fig. 2

Satisfaction level with the old-age allowance policy

Fig. 3

Satisfaction levels with the special treatment for disabilities policy

Fig. 4

Satisfaction levels with the land transportation policy

Fig. 5

Satisfaction levels with the water transportation policy

Fig. 6

Satisfaction levels with the air transportation policy

Fig. 7

Satisfaction levels with the disaster early warning policy

Fig. 8

Satisfaction levels with the emergency assistance systems policy

Appendix B

This section examines the effects of aging on satisfaction levels with public policies related to the health system, old-age allowances, and special treatment for disabled people using various econometric methods, including the OLOGIT, OPROBIT, OLS, and GOLM.

B.1 Old-Age Population and Public Policies Related to the Health System

Table 5 shows the analysis results examining how age affects satisfaction levels with government policies related to the health system. It includes results from OLOGIT (second column), OPROBIT (third column), and OLS (last column) models. We also implement the GOLM and present the results separately in Table 6.

Table 5 The effects of age on satisfaction with public policies related to the health system using various econometric methodsTable 6 The effects of age on satisfaction with public policies related to the health system using GOLM

The findings in Table 5 consistently show that increasing age is linked to a significantly higher probability of greater satisfaction with public health policies. Specifically, each additional year of age raises satisfaction by approximately 0.015, 0.007, and 0.002 in the OLOGIT, OPROBIT, and OLS models, respectively. These results are consistent with prior research, such as that of Calnan et al. (2003), indicating that older individuals are more satisfied with public health policies. This pattern reflects the positive attitude of older adults toward public services, especially healthcare. It also highlights the preference of the older population for healthcare-related public policies, as they may want the government to sustain or enhance services in this area.

However, some demographic and socio-economic factors seem to influence satisfaction levels differently. Male respondents, individuals living in Bangkok, and those with higher education levels are likelier to report lower satisfaction with public health policies. Additionally, respondents who rate their physical health higher (on a scale of 1 to 5, with 5 being the best) are more likely to be dissatisfied with policies related to the health system. This suggests that individuals with better physical health may rely less on public health services and perceive them as less relevant to their needs.

Respondents who reported better mental health scores expressed greater satisfaction with government-provided health policies. This finding aligns with the observation that aging populations typically advocate for improved access to affordable healthcare, comprehensive health insurance coverage, and increased funding for medical research targeting age-related diseases.

The proportional odds assumption in ordinal logistic regression implies that the relationship between each pair of outcome groups is consistent. Specifically, it assumes that the odds ratios comparing the different levels of the outcome variable remain constant across the levels of the predictor variables. The Brant test, introduced by Brant (1990), evaluates whether this assumption holds. If the proportional odds assumption is violated (we do the Brant test prior to employing the GOLM model), alternative models like GOLM may better suit the data, and we will see that the estimates are different across categories when we relax the proportional odds assumption (Brant, 1990).

In addition to the Brant test, other statistical tests, such as the likelihood ratio test, Lagrange multiplier test, and Wald test, can be used to assess the performance of ordinal logistic regression models. These tests evaluate broader aspects, such as model fit and error distribution. However, given the focus of this manuscript on the proportional odds assumption, the Brant test is employed due to its straightforward interpretation and widespread use among researchers.

Table 6 compares the results of the Ordered Logit Model (OLOGIT) with GOLM. For instance, in Model 1 (OLOGIT), the variable AGE assumes the same slope (coefficient value) across all categories. However, in Model 2 (GOLM), the results show that the odds of being strongly dissatisfied (SD) with public policies related to the health system versus the combined categories of dissatisfied (D), satisfied (S), and strongly satisfied (SS) are 1.005 times greater for a one-unit increase in age, holding all other variables constant. Despite this finding, the statistical significance is lost.

Moreover, when examining the odds of being in the combined categories of SD and D versus S and SS, a one-unit increase in age results in odds that are 1.016 times greater (compared to 1.015 in OLOGIT), ceteris paribus. Similarly, the odds of being in the combined categories of SD, D, and S versus SS increase by 1.014 times for a one-unit increase in age, holding other variables constant.

Although the GOLM reveals differences in the probabilities of transitioning between satisfaction levels, the overall results are consistent with those of the OLOGIT model, reaffirming the positive effects of age on public policy satisfaction. This consistency highlights the robustness of the findings across different modeling approaches.

B.2 Old-Age Population and the Old-Age Allowance Policy

This section applies the same econometric approaches to analyze the relationship between age and satisfaction levels with the old-age allowance policy. The coefficient of age indicates that for each one-year increase above age 50, the probability of being satisfied with the universal old-age allowance increases by 0.012, holding all other variables constant. In other words, a one-unit increase in age raises the ordered log odds of being in a higher satisfaction category by 0.012Footnote 1, which is statistically significant, assuming all other variables remain unchanged.

Similarly, a one-unit increase in age results in the odds of being in the combined categories of Strongly Dissatisfied (SD) and Dissatisfied (D) versus Satisfied (S) and Strongly Satisfied (SS) increasing by 1.012 times, ceteris paribus. Likewise, the odds of being in the combined categories of SD, D, and S versus SS increase by 1.012 times for a one-unit increase in age, holding other variables constant. These findings confirm the positive effects of age on public policy preferences across the different econometric methods employed in this study.

The results align with findings by Lloyd-Sherlock et al. (2012), who demonstrated that transfer benefits, such as old-age allowances, substantially boost per capita income and contribute to overall well-being satisfaction. Reported levels of subjective satisfaction do not decline with age, and there is notable optimism regarding future well-being. Enhanced health services and targeted policies, such as improved credit access, further reinforce the positive impact of public services on household satisfaction.

Table 7 demonstrates the consistency of results across econometric methods. For the OPROBIT model, a one-unit increase in age increases the probability of higher satisfaction with the old-age allowance policy by 0.006. Using the OLS model, the increase in satisfaction is estimated at 0.003 for each additional year of age.

Table 7 The effects of age on satisfaction with the old-age allowance policy using various econometric methods

The results indicate that males report lower satisfaction levels with public policies in general, and individuals living in the capital city, Bangkok, are less likely to be satisfied with the old-age allowance policy. In contrast, respondents from outside Bangkok are more likely to express satisfaction with this policy. This discrepancy may be attributed to regional differences in living costs. The old-age allowance provides individuals aged 60 and above with approximately 16 USD per monthFootnote 2, with an incremental increase of about 2.80 USD for every additional decade of age. While this amount may contribute meaningfully to household income in rural areas, it is insufficient to cover the average monthly living cost in Bangkok, which is estimated to be around 615 USDFootnote 3.

As with health-related public policies, education significantly shapes satisfaction levels with the old-age allowance. Respondents with higher education levels, particularly those transitioning from elementary or lower to high school, are less satisfied with the policy. However, individuals with undergraduate degrees report greater satisfaction than high school graduates, potentially because they are less reliant on the allowance due to higher average incomes.

Income and family support also appear to influence satisfaction levels. Older adults with higher annual incomes or financial support from their children are more likely to be satisfied with the old-age allowance. Regarding self-reported health, individuals with higher physical health scores report lower satisfaction with the policy. Conversely, respondents with higher self-rated mental health scores are more likely to express satisfaction, suggesting that mental well-being may shape perceptions of government support.

To address potential violations of the parallel regression assumption, we applied GOLM, which offers greater flexibility by relaxing this assumption. Table 8 presents the results of the GOLM (Model 2), allowing for varying slopes across satisfaction categories.

Table 8 The effects of age on satisfaction with the old-age allowance policy using GOLM

For example, the variable AGE shows that, instead of assuming the same slope for all satisfaction levels (as in Model 1), the odds of being strongly dissatisfied (SD) with the old-age allowance policy versus the combined categories of dissatisfied (D), satisfied (S), and strongly satisfied (SS) are 1.001 times greater for a one-unit increase in age, holding other variables constant. However, this result is not statistically significant. Similarly, the odds of being in the combined categories of SD and D versus S and SS increase by 1.010 times for a one-unit increase in age. The same pattern holds for the odds of being in the combined categories of SD, D, and S versus SS, which suggests that for every one-unit increase in age, the probability of a change in the satisfaction level to strongly satisfied is 0.014, or the odds are 1.014 times for a one-unit increase in age.

While the GOLM highlights differences in probabilities between satisfaction levels, the results remain consistent with the findings from OLOGIT. For other variables, such as income per year and self-rated physical health scores, the GOLM confirms the OLOGIT results, reinforcing the robustness of our conclusions.

B.3 Old-Age Population and Public Policies Related to Special Treatment for Disabilities

This section examines the relationship between age and satisfaction levels with public policies supporting disabled individuals, employing various econometric methods for robustness checks. Table 9 presents the results from OLOGIT, OPROBIT, and OLS. Overall, the findings indicate that age positively affects satisfaction levels with disability-related policies, though the magnitude is smaller compared to health-related policies and the old-age allowance. Interestingly, the effect of gender is no longer statistically significant in the context of policies for disabled individuals. However, regional differences persist. Respondents residing in Bangkok and the Central region are less likely to express satisfaction with disability-related policies, unlike those from Northern Thailand, who report higher satisfaction. This discrepancy may stem from the density and infrastructure of Bangkok and its surrounding areas, which may be less accommodating to the needs of older adults and disabled individuals. As with other public policies, education level plays a role in shaping satisfaction levels. Respondents with higher levels of education generally report higher satisfaction with disability-related policies. However, for individuals with undergraduate degrees or higher, the impact of public services appears to diminish, potentially because these respondents are less reliant on such services due to greater access to private resources.

Table 9 The effects of age on satisfaction with public policies related to special treatment for disabilities using various econometric methods

We conducted the GOLM and compared its results to those from the conventional OLOGIT. Table 10 presents how age influences satisfaction levels with public policies supporting disabled individuals. Relaxing the parallel regression assumption through GOLM allows for a more nuanced interpretation of the effects of age on satisfaction levels. In Model 1 (OLOGIT), age positively affects the probability of higher satisfaction with public policies, holding other variables constant. In contrast, Model 2 (GOLM) provides additional insights, showing that age not only increases satisfaction but that this effect becomes significantly stronger as individuals grow older. This suggests that older respondents are more appreciative of policies tailored to the needs of disabled individuals, particularly as they themselves face increased physical challenges with age. Regarding self-reported physical health, respondents who perceive themselves as physically healthy tend to be less satisfied with disability-related policies. The GOLM further reveals that this dissatisfaction is more pronounced among those who rate their physical condition highly. This may indicate that healthier individuals perceive these policies as less relevant to their immediate needs than respondents with poorer health.

Table 10 The effects of age on satisfaction with public policies related to special treatments for disabilities using GOLM