We find that individuals’ opinions concerning protectionist policies match with how their revenue could be affected in the medium or long term by trade liberalisation in line with predictions of the comparative advantage models. An adverse macroeconomic context (large increase in the unemployment rate or inflation rate) increases protectionist attitudes, thus reflecting that people do not trust that free trade will lead to lower prices or create jobs despite trade theory optimism. People share a mercantilist view of trade since more imports increase protectionism support, while people positively value exports, especially in small countries. Regarding policy measures, while protectionist measures do not influence protectionism support in general, easy access to exports reduces people’s support for protectionism.
Trade restriction levels applied by countries are strongly correlated with average support for protectionism among residents. But what elements shape these individuals’ attitudes? Protectionism support depends not only on noneconomic factors such as values and demographic characteristics but also on the labour market and the macroeconomic situation. In this study, we examine some yet-to-be-studied factors that may influence opinions towards trade policies. We hypothesise that individual support for protectionism is not only affected by the above-mentioned factors but also by the macroeconomic context, importance of trade and size of the country, trade policies applied by the resident’s country on its imports, and trade policies applied by other countries on exports of the resident’s country.
The International Social Survey Programme (ISSP) survey of 2003, which is available for more than thirty countries, offers a good opportunity to study reasons for protectionism support. To investigate this issue, we explain protectionism support using an ordered probit model that includes individual attributes and country characteristics.
We build on the existing literature and bring new elements into the discussion. First, we test the influence of macroeconomic variables such as gross national income (GNI) per capita, inflation, unemployment rates, and risk index on individual attitudes. Second, we check if individual support for protectionism is in line with the predictions of comparative advantage models. Third, we study the link between import and export shares in GDP and individual opinions towards trade. Finally, we study how trade restrictions on imports influence individual attitudes and if access granted to country exports has an impact on his/her position. To anticipate our most important results, we find that individuals’ opinions concerning protectionist policies match with how their revenue could be affected in the medium or long term. In turn, we find evidence that people’s appreciation of the consequences of trade liberalisation for the whole economy is not in line with trade theory optimism for free trade. Finally, strengthening exports or access to export products reduces protectionist pressures.
The structure of the paper is as follows. In Section
Support for protectionism may therefore be explained by the impact of trade on individual income. Comparative advantage models explain how international trade affects personal income through changes in relative prices. The Heckscher-Ohlin model (H-O) assumes complete costless factor mobility across sectors and is often presented as a long-run view. In contrast, the Ricardo-Viner model (R-V) assumes the existence of sector-specific factors and for this reason is often presented as a medium-term model. According to the H-O model, unskilled workers in unskilled-labour-abundant countries are expected to support free trade, while skilled workers would be expected to oppose it. The opposite would occur in skill-abundant countries. On the other hand, the R-V model predicts that specific factors of the importing sector will lose out from trade liberalisation, but factors specific to the export sector will gain from it. Given that labour is not very mobile across sectors in the short term, individual trade policy preferences will depend on whether the person is employed in an import-substituting or exporting industry [
Although empirical studies confirm that trade policy preferences depend on individuals’ skills, the results of these studies are not fully in line with the H-O model. O’Rourke and Sinnott [
The literature focusing on the influence of the macroeconomic context on protectionism attitude is scarce. Denslow and Fullerton [
Another relation that has received very little attention in the literature is how the trade balance situation or trade policies influence people’s opinion towards these policies. As regards opinion polls, trade restriction levels are found to be strongly correlated with average support for protectionism among residents. Nevertheless, the direction of the causal relationship between preferences for protectionism and trade policies is not clear. Policymakers may design policies bearing in mind public opinion, that is, according to the “demand” side. Yet trade policies may, in turn, lead to biased attitudes towards trade policies. As suggested by Mayda and Rodrik [
Opinions towards trade policies are obviously linked to labor market’s situation of respondents. People with higher educational levels anywhere in the world may be more flexible and more able to deal with the rigors of the market and therefore more likely to support trade liberalisation [
Previous literature has demonstrated that trade policy preferences depend on noneconomic factors such as values and demographic characteristics. Concerning the influence of religious beliefs, Guiso et al. [
Undoubtedly, attachment to country and national pride matters in any debate concerning external policies. O’Rourke and Sinnott [
Finally, there are many demographic variables that may be relevant in explaining policy preferences. For example, in regard to age and gender, previous empirical studies have shown that the elderly are more likely to support import restrictive policies than younger people. The same can be said for women in comparison to men. Additionally, some empirical studies, [
In this paper we use data from the National Identity module of the 2003 International Social Survey Program (ISSP) to study how the different characteristics of both individuals and countries affect support for protectionism. The ISSP is an ongoing effort devoted to cross-national research on social attitudes. The survey asks respondents about their opinions on a great variety of issues, including trade preferences. As previous studies have already shown, the ISSP survey allows the influence of social status, relative income, values, and attachments on preference formation to be explored (unfortunately, this question has not been included in the other waves of the survey. It is therefore impossible to run panel estimations or to study the evolution of the position of the same countries through time).
The respondents came from 33 countries across all five continents (Germany and Israel were included whole countries even though they are both included in the dataset as two regions. Due to the lack of data on income, South Africa and Venezuela were not included). The ISSP dataset provides a unique opportunity to verify all the hypotheses emerging from the previous review of the literature. Additionally, researchers can test if individuals react according to how specialisation affects their personal revenue. The survey also offers a less investigated possibility, namely, to verify to what extent the heterogeneity observed across individuals in their support for protectionism may be explained by some economic characteristics of their place of residence. We estimate ordered probit models in which the degree of protectionism support is explained by personal attributes as previous works do, and we also add important country characteristics.
The question used in the survey to identify respondents’ trade preferences is “how much do you agree or disagree with the following statement: “Respondent’s country’’ should limit the import of foreign products in order to protect its national economy.” The dependent variable (PROTEC) that corresponds to the answer is coded as follows: three agree or strongly agree, two neither agree nor disagree, and one disagrees or strongly disagrees. Mayda and Rodrik [
It could be argued that the last part of the question (“in order to protect its national economy”) leads to biased responses in favour of protectionism as it implies that limiting imports is a way of protecting the economy and is therefore something positive. However, there are two arguments that partially detract from this criticism. Firstly, this is the usual manner of speech employed to defend protectionist policies and thus the normal terms used to discuss the matter. Hence, this question would not necessarily induce the respondent to answer in a particular way. And secondly, because the goal of this paper is to analyse the relationship between this variable and others and not to estimate the absolute level of support for protectionism, our analysis is less vulnerable to this type of bias [
On average, about 1,000 people have answered the survey in each country, obtaining a total of 42,154 observations. Table
Answers by country.
Country | ISO3 code | No protect | Protect | Neutral |
---|---|---|---|---|
Australia (omitted) | AUS | 14.5 | 66.1 | 19.4 |
Austria | AUT | 23.5 | 58.8 | 17.7 |
Bulgaria | BGR | 11.5 |
|
12.1 |
Canada | CAN | 26.2 | 51.4 | 22.4 |
Chile | CHL | 21.9 | 63.5 | 14.6 |
Czech-Republic | CZE | 27.1 | 50.6 | 22.2 |
Denmark | DNK |
|
35.6 | 16.4 |
Finland | FIN | 38.4 | 34.0 | 27.6 |
France | FRA | 27.8 | 51.7 | 20.5 |
Germany | DEU | 33.0 | 44.3 | 22.7 |
Great Britain | GBR | 16.2 | 59.4 | 24.3 |
Hungary | HUN | 13.3 | 65.3 | 21.4 |
Ireland | IRL | 27.6 | 57.7 | 14.7 |
Israel | ISR | 22.4 | 62.7 | 14.9 |
Japan | JPN | 28.4 | 40.8 | 30.8 |
Latvia | LVA | 15.9 | 66.9 | 17.2 |
New Zealand | NZL | 21.3 | 57.0 | 21.7 |
Norway | NOR | 36.4 | 35.1 | 28.5 |
Philippines | PHL | 11.6 | 72.7 | 15.7 |
Poland | POL | 12.1 | 71.9 | 15.9 |
Portugal | PRT | 21.6 | 63.8 | 14.6 |
Russia | RUS | 20.2 | 63.6 | 16.2 |
Slovak Republic | SVK |
|
65.8 | 24.7 |
Slovenia | SVN | 28.3 | 52.9 | 18.8 |
South Korea | KOR | 24.7 | 52.6 | 22.7 |
Spain | ESP | 14.7 | 59.5 | 25.8 |
Sweden | SWE | 35.3 |
|
35.8 |
Switzerland | CHE | 43.4 | 36.7 | 19.9 |
United States | USA | 17.2 | 61.4 | 21.4 |
Uruguay | URY | 13.0 | 73.1 | 13.9 |
Source: ISSP, values in percentages.
Concerning personal attributes, we include earnings in logarithms (log of income) and a subjective evaluation by the individual regarding his or her social status (upper class). We expect both variables to decrease the probability of supporting protectionism. In turn, patriotism and nationalism (pride and chauvinism) are expected to increase support for protectionism. As concerns demographic variables, we consider age (age and age2) and gender (female), which usually strengthen the protectionist view. We hypothesise that personal skill (measured by years of schooling) generally decreases support for protectionism. Note that our sample includes high, middle, and lower-middle income countries (according to the World Bank classification, Atlas Method). Our sample is less biased towards rich countries than the 1995 ISSP used in Mayda and Rodrik [
Description of variables.
Variable name | Variable label | Data source |
---|---|---|
ADV | 1 if employment sector comparative advantage is strong |
ISSP (2003)/CEPII [ |
Age | Respondent’s age | ISSP (2003) |
Age2 | Age |
ISSP (2003) |
Agriculture | 1 if working in agricultural sector | ISSP (2003) |
Attend religion | 1 if attends religious services once a week or more | ISSP (2003) |
Chauvinism | 1 if agreeing with “generally speaking, your country is a better country than most other countries” | ISSP (2003) |
CAI | Comparative Advantage Index, mean 1980–2001 | ISSP (2003)/CEPII [ |
CPI (change) | Logarithm of (1 + the change in inflation rate) | World Bank [ |
DADV | 1 if employment sector comparative disadvantage is strong | ISSP (2003)/CEPII [ |
EDUYEARS | Years of schooling | ISSP (2003) |
EDUIPC | EDUYEARS |
ISSP (2003)/ World Bank [ |
Female | 0 for men and 1 for women | ISSP (2003) |
High | 1 if LGNIpc is higher than 9.2 (equivalent to US$ 10,000) | World Bank [ |
Industry | 1 if working in industrial sector | ISSP (2003) |
Large | 1 if the number of inhabitants is higher than 30 million | World Bank [ |
LGNIpc | Logarithm of Gross National Income per capita, Atlas method (current US$) | World Bank [ |
LINCOME | Logarithm of earnings | ISSP (2003) |
LMAOTRI | Logarithm of Market Access Overall Trade Restrictiveness Index (tariffs and nontariff barriers) | Anderson and Neary [ |
LMRATIO | Logarithm of imports of goods and services (percentage GDP, 2000–2004 average) | World Bank [ |
LOTRI | Logarithm of Overall Trade Restrictiveness Index (tariffs and nontariff barriers) | Anderson and Neary [ |
LXRATIO | Logarithm of exports of goods and services (percentage GDP, 2000–2004 average) | World Bank [ |
Middle | 1 if LGNIpc is lower than 9.2 (equivalent to US$ 10,000) | World Bank [ |
Pride | 1 if feeling proud of country | ISSP (2003) |
Risk | Logarithm of country risk | SACE (2004) |
Service | 1 if working in service sector | ISSP (2003) |
Small | 1 if the number of inhabitants is 30 million or lower | World Bank [ |
Trade | Logarithm of external balance of payments as percentage of GDP | World Bank [ |
Unemployment rate (change) | Logarithm of (1 + the change in unemployment rate) | World Bank [ |
Upper class | 1 if self-placement on 10-point income scale is between 6 and 10 | ISSP (2003) |
To the end that products including a higher level of capital per worker are more willing to operate under increasing returns, we expect richer countries to obtain more gains from trade. We include
Figure
Share of persons supporting protectionism and GNI per capita. Note: ISO3 country abbreviations are reported in Table
As business cycles may influence respondents’ sensitivity to trade policies,
Finally, Denslow and Fullerton [
We need to verify if the people in our sample react according to the H-O and R-V theories. In order to check the Stolper-Samuelson theorem hypothesis, we interact the variable EDUCYRS with the logarithm of per capita GDP as in Mayda and Rodrik [
In order to test the predictions of the R-V models, we reclassify the information concerning the
The impact of trade balance on protectionist views has not yet been studied. We argue that a high import penetration rate (MRATIO) could reflect a large level of dependency on foreign products and should be associated with strong support for liberalisation. However, the relationship between imports and proprotectionism may be more complex. The MRATIO also depends on trade policies. That is, a low penetration rate can reflect a very strong protectionist policy. In this case, a lower MRATIO may increase support for protectionism. In both of the previous cases, the relationship between MRATIO and PROTEC should be negative. In turn, if the presence of foreign products in the domestic market is perceived as an invasion of the domestic market, it may increase the demand for a protectionist policy. In this case, the relationship between MRATIO and PROTEC would be positive.
In the same line, the export ratio (XRATIO) has not been accounted for in the related literature. As far as national protectionist measures can be seen as a counterpart to the difficulties of exporting, a lower XRATIO should increase the support for protectionism.
The MRATIO is introduced to reflect the dependency of the country on international products from the demand side. XRATIO reflects the dependency of the country on international products from the supply side. MRATIO and XRATIO were obtained from the World Bank Database and included in log terms. In Figure
Share of persons supporting protectionism and import penetration. Note: ISO3 country abbreviations are reported in Table
We use the
The relationship between trade policy instruments and protectionism support is not homogeneous (Figure
Share of persons supporting protectionism and trade policy. Note: ISO3 country abbreviations are reported in Table
In highly protected economies, people may value the inconveniences of such policies more highly or, in contrast, they may fear the costs of liberalisation. The expected sign for the coefficient of OTRI is thus undetermined. Additionally, since restrictive policies are explained to a larger extent by high protectionism support, this index may suffer an endogenous bias. We also control for this possible bias using instrumental variables for OTRI. Concerning MAOTRI, it is likely that residents in the exporting country will unanimously consider the effect of better access to international markets as being positive. Yet their level of awareness about these measures and how far this sentiment is connected to their support for national protectionism is less clear. If support for protectionism increases (significant positive sign) when there are difficulties to export, it will demonstrate that exports are viewed as a counterweight to the removal of national restrictions.
In this section we study the impact of different individual and country characteristics on individual protectionism support. Our results concerning the influence of personal characteristics are standard. Specifically, we find that people with the characteristics “religious attendance,” “low social status,” “low personal income,” “pride,” “chauvinism,” and “female” are more prone to support protectionist policies. Unlike other studies, we find that age, when significant, decreases protectionism support and the coefficient of age squared is almost zero, indicating that this effect is constant. In general, our conclusions are similar to those of Daniels and von der Rhur [
Since these results are well known, in what follows we focus on the impact of country characteristics on individual support for protectionism, the most original contribution of our study. The influence of macroeconomic variables is discussed in Section 3.2. We provide an empirical verification for the predictions of the comparative advantage models and new trade theory in Section 3.3. Finally, Section 3.4 analyses the impact of trade policy.
Table
Protectionism opinion—oprobit models with country dummies.
3.1—personal attributes | 3.2—model 3.1 plus GDP per capita | 3.3—model 3.1 plus inflation | 3.4—model 3.1 plus change in unemployment rate | 3.5—model 3.1 plus country risk | 3.6—model 3.2 considering income level | 3.7—model 3.3 considering income level | 3.8—model 3.4 considering income level | 3.9—model 3.5 considering income level | |
---|---|---|---|---|---|---|---|---|---|
Probability | 55.44% | 55.44% | 55.04% | 55.44% | 55.44% | 55.44% | 55.44% | 55.04% | 55.44% |
Female | 0.069*** | 0.069*** | 0.069*** | 0.069*** | 0.082*** | 0.069*** | 0.069*** | 0.069*** | 0.082*** |
(0.009) | (0.010) | (0.009) | (0.009) | (0.011) | (0.009) | (0.009) | (0.009) | (0.011) | |
Age | −0.002 | −0.002 | −0.003* | −0.002 | −0.004* | −0.002 | −0.002 | −0.003* | −0.004** |
(0.002) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | |
Age2 | 0.000* | 0.000* | 0.000** | 0.000* | 0.000** | 0.000* | 0.000* | 0.000** | 0.000*** |
(0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | |
EDUYRS | −0.019*** | −0.019*** | −0.020*** | −0.019*** | −0.020*** | −0.019*** | −0.019*** | −0.020*** | −0.020*** |
(0.002) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | |
Upper class | −0.023** | −0.023** | −0.022*** | −0.023** | −0.028** | −0.023** | −0.023** | −0.022** | −0.028*** |
(0.010) | (0.010) | (0.010) | (0.010) | (0.010) | (0.010) | (0.010) | (0.010) | (0.010) | |
LINCOME | −0.046*** | −0.046*** | −0.044*** | −0.046*** | −0.015 | −0.046*** | −0.046*** | −0.044*** | −0.015 |
(0.010) | (0.010) | (0.010) | (0.010) | (0.015) | (0.010) | (0.010) | (0.010) | (0.015) | |
Attend religion | 0.053*** | 0.053*** | 0.054*** | 0.053*** | 0.063*** | 0.053*** | 0.053*** | 0.054*** | 0.064*** |
(0.012) | (0.012) | (0.012) | (0.012) | (0.013) | (0.012) | (0.012) | (0.012) | (0.013) | |
Chauvinism | 0.087*** | 0.086*** | 0.087*** | 0.087*** | 0.096*** | 0.087*** | 0.087*** | 0.087*** | 0.096*** |
(0.011) | (0.011) | (0.011) | (0.011) | (0.011) | (0.011) | (0.011) | (0.011) | (0.011) | |
Pride | 0.145*** | 0.145*** | 0.145*** | 0.145*** | 0.145*** | 0.145*** | 0.145*** | 0.144*** | 0.145*** |
(0.011) | (0.011) | (0.012) | (0.012) | (0.011) | (0.011) | (0.011) | (0.011) | (0.011) | |
LGNIPC | 0.129** | ||||||||
(0.059) | |||||||||
CPI (change) | 0.311*** | ||||||||
(0.015) | |||||||||
Unemployment rate (change) | 0.340** | ||||||||
(0.157) | |||||||||
Risk | 0.051 | ||||||||
(0.055) | |||||||||
LGNIPC |
0.129** | ||||||||
(0.059) | |||||||||
LGNIPC |
0.160** | ||||||||
(0.076) | |||||||||
Unemployment rate (change) |
0.340** | ||||||||
(0.157) | |||||||||
Unemployment rate (change) |
0.270** | ||||||||
(0.107) | |||||||||
CPI (change) |
0.980*** | ||||||||
(0.109) | |||||||||
CPI (change) |
0.168*** | ||||||||
(0.027) | |||||||||
Risk |
0.051 | ||||||||
(0.055) | |||||||||
Risk |
0.089** | ||||||||
(0.045) | |||||||||
Observations | 23159 | 23159 | 23159 | 23159 | 23159 | 23159 | 23159 | 23159 | 23159 |
Pseudo |
0.08 | 0.08 | 0.08 | 0.08 | 0.07 | 0.08 | 0.08 | 0.08 | 0.08 |
Robust standard errors in brackets.
All models include dummy variables per country of residence.
We reach the unexpected results that support for protectionist measures increases with the GNI per capita of the country once country specificity is controlled for. The same result is obtained when we take into account the growth rate of the GNI per capita instead of the level. Thus, GNI per capita turns negative when we drop dummies for countries (these results are not reported here, but are available upon request). Therefore, people in rich countries are less likely to offer support for the protectionist view, although this is already taken into account with the countries’ dummies.
Our results show that support for protectionism increases when inflation pressures become high despite the fact that trade liberalisation would rationally push prices down. It therefore seems that inflation rate, insofar as it reflects macroeconomic instability, may increase protectionism pressure. An increase in unemployment rate also increases protectionist attitudes. These results confirm that the business cycle influences opinions towards trade policies. A large increase in unemployment rate or inflation rate increases protectionist attitudes, especially in high-income countries.
In turn, we find that the global market risk index has no statistically significant effect, thus indicating that neither free trade nor protectionism is viewed as a solution for market instability. In turn, protectionism is viewed as a solution when market risk increases in middle-income countries.
In Table
Protectionism opinion—verification of trade theory predictions.
4.1—interaction effects, H–O model | 4.2—the effects of education per country size | 4.3—with activity sectors | 4.4—with comparative advantage index | 4.5—with comparative (dis)advantage | |
---|---|---|---|---|---|
Probability | 55.38% | 55.4% | 55.79% | 55.44% | 55.44% |
EDUYRS | −0.024** | −0.024** | −0.018* | −0.023** | −0.023** |
(0.010) | (0.010) | (0.010) | (0.010) | (0.010) | |
LGNIPC | 0.250*** | ||||
(0.064) | |||||
EDUIPC | −0.008*** | ||||
(0.002) | |||||
EDUYRS |
−0.023*** | ||||
(0.002) | |||||
EDUYRS |
−0.008** | ||||
(0.004) | |||||
Industry | 0.049*** | ||||
(0.015) | |||||
Agriculture | 0.117*** | ||||
(0.039) | |||||
Service | 0.026** | ||||
(0.013) | |||||
CAI | −0.001** | ||||
(0.000) | |||||
ADV | 0.012 | ||||
(0.025) | |||||
DADV | 0.060*** | ||||
(0.016) | |||||
Observations | 23159 | 23159 | 23159 | 23159 | 23159 |
Pseudo |
0.08 | 0.08 | 0.08 | 0.08 | 0.08 |
*Significant at 10%; **significant at 5%; ***significant at 1%. Source: see Table
Robust standard errors in brackets.
All models 3.2 include dummy variables per country of residence.
All models include the same set of control variables not included in Table
Interaction effect between education and gross domestic product (per capita, in logs).
We test several predictions in line with the R-V model. In model 4.6 we include dummies for the respondents’ activity sector (agriculture, industry, and services). Surprisingly, we find that all three sectors have a significant positive impact, suggesting that workers are, on average, more supportive of protectionist measures than nonworkers. Specifically, we expected people working in the services sector not to be protectionist. Nonetheless, the marginal effects of these variables are more in line with our predictions since the highest impact is found in the case of agriculture (generally more protected) followed by industry and services. Interacting the variables of the employment sector with dummies indicating the country, we obtain that protectionist attitudes in the agricultural sector mainly come from people employed in this sector in small countries.
To test the R-V model more precisely, in model 4.6 and model 4.7 we account for the comparative advantage or disadvantage (calculated in reference to the world trade structure) of the sector in which the respondents are working. Firstly, we consider a continuous variable, the Comparative Advantage Index. Secondly, we build two dummies corresponding to the comparative advantage and comparative disadvantage cases. The results show that working in a sector with a comparative advantage decreases protectionist support, while working in a disadvantaged sector has a positive and significant effect. Our results unambiguously support the R-V model, which is often presented as a medium-term view of trade effects.
The intensity of international trade integration may play an important role in the way citizens shape their preferences towards trade policies. In what follows, we turn to the influence of international trade on protectionist opinions. The results shown in Table
Trade impact on individual opinion towards protectionism.
5.1—import penetration rate and export ratio | 5.2—balance of payments | 5.3—model 5.1 considering country size | 5.4—model 5.2 considering country size | |
---|---|---|---|---|
55.44% | 55.44% | 55.44% | 55.44% | |
EDUYRS | −0.019*** | −0.019*** | −0.019*** | −0.019*** |
(0.002) | (0.002) | (0.002) | (0.002) | |
LXRATIO | −0.867*** | |||
(0.161) | ||||
LMRATIO | 0.882*** | |||
(0.212) | ||||
Trade | −0.102** | |||
(0.045) | ||||
LXRATIO |
−0.122 | |||
(0.141) | ||||
LXRATIO |
−0.655*** | |||
(0.144) | ||||
LMRATIO |
−0.222 | |||
(0.170) | ||||
LMRATIO |
0.367** | |||
(0.173) | ||||
Trade |
−0.296*** | |||
(0.033) | ||||
Trade |
−346.662*** | |||
(93.516) | ||||
Observations | 23159 | 23159 | 23159 | 23159 |
Pseudo |
0.08 | 0.08 | 0.08 | 0.08 |
*Significant at 10%; **significant at 5%; ***significant at 1%. Source: see Table
All models include the same set of control variables not included in Table
Larger markets could benefit from a market power that enables them to increase their term of trade by increasing the static gains of protection. In contrast, inhabitants of small countries could be aware of their dependency on foreign products and more reluctant to use protectionist measures even when external trade represents a large share of their economic activity. To test this hypothesis, in models 5.3 and 5.4 we interact MRATIO, XRATIO, and TRADE with dummies indicating the size of the country. Our results confirm that the presence of foreign products or the importance of export activities is decisive for inhabitants of small countries, but not so important for people living in large countries. Trade deficit increases protectionist views, particularly in these small countries.
In our benchmark model we include trade policy indicators (Table
Trade policy impact on individual opinion towards protectionism.
6.1—overall trade restrictiveness index and market access index | 6.2—model 6.1 plus OTRI instrumented | 6.3—overall trade restrictiveness index considering country size and market access index | 6.4—overall trade restrictiveness index and market access index considering country size | |
---|---|---|---|---|
Probability | 55.08% | 55.85% | 55.08% | 55.05% |
EDUYRS | −0.020*** | −0.020*** | −0.020*** | −0.020*** |
(0.002) | (0.002) | (0.002) | (0.002) | |
LOTRI | 0.447 | 1.349** | ||
(0.341) | (0.646) | |||
LMAOTRI | 0.975*** | 17.505*** | 0.677* | |
(0.166) | (4.542) | (0.395) | ||
LOTRI instrumented | 33.145*** | |||
(9.534) | ||||
LOTRI |
−0.113 | |||
(0.108) | ||||
LOTRI |
−0.802 | |||
(0.655) | ||||
LMAOTRI |
1.285** | |||
(0.682) | ||||
LMAOTRI |
1.164 | |||
(0.860) | ||||
Observations | 18905 | 18905 | 18905 | 18905 |
Pseudo |
0.08 | 0.08 | 0.08 | 0.08 |
*Significant at 10%; **significant at 5%; ***significant at 1%. Source: see Table
All models include the same set of control variables not included in Table
The theory of protection shows that trade policy instruments do not have the same impact on a small or large country. In fact, a large demand or supply of a large country enables the country to influence international prices and could make duties on imports or subsidies for exports more optimal in this case. According to this economic logic, people living in big countries should be more protectionist. To check if people are aware of this argument, we interact the trade policy indicators with a dummy indicating the size of the country. We find that a high level of protection does not have an influence on individual support for protectionism in small or large countries. When we split the MAOTRI index into two variables according to the size of the countries, we observe that the access granted to exports increases protectionism support in small countries. People value the facilities given or restrictions imposed by their trading partners when making decisions concerning their own trade policy and this is especially true for small countries.
In this study, we hypothesise that individual support for protectionism is not only affected by noneconomic factors, such as the respondent’s attachment or nationalism values or personal economic situations, but also by some macroeconomic factors. To test our proposal, we explain protectionism support using an ordered probit model that includes individual attributes and country characteristics. We use data on individual preferences for free trade from the ISSP survey. Unfortunately, the version of ISSP that includes the preference concerning free trade is only available for the year 2003. Although these data are somewhat dated, they are the most recent to test our hypotheses. The dataset is available for more than thirty countries and offers a very interesting database for our purpose. We complete this rich database with a wide range of macroeconomic indicators collected from different databases. In particular, we use indicators concerning macroeconomic context (GNI per capita, inflation, unemployment rates, and risk index), importance of trade and size of the country, and, more originally, indicators concerning the restrictiveness of trade policies for imports and exports.
Some of our conclusions are similar to those of Daniels and von der Rhur [
Our main contribution consists in testing the influence of some macroeconomic factors on individual preferences for free trade. We find evidence that their overall appreciation of the consequence of trade liberalisation for the whole economy is not in line with trade theory optimism for free trade. A large increase in the unemployment rate or inflation rate increases protectionist attitudes, indicating that individuals do not trust that free trade will lead to lower prices or create jobs. In an unstable macroeconomic context, the fear of adjustment costs outweighs the positive effect that free trade could bring through a reallocation of resources.
We test if protectionism support is influenced by the dependence of the individuals’ country of residence on external trade as reflected in the import penetration rate and export ratio. We find a positive relation between the import penetration rate and protectionism support, especially in small countries. In other words, foreign products are seen as a threat for national production rather than an opportunity for consumers. Our results suggest that people reject the possibility that trade liberalisation could alleviate the balance of payments problem in dependent countries by lowering prices. In the same line, people positively value exports, especially in small countries. Hence, our results offer clear proof that the public does not embrace free trade and Smith’s laissez-faire, at least through a more neomercantilism view which considers that a favourable balance of trade is associated with a healthy economy; a situation that should be reached according to this view through protectionism measures.
We also confirm that trade restriction levels applied by countries are positively correlated with average support for protectionism among residents. One explanation for this is that trade policies respond to public demands. We also test if trade policies in turn influence public demand for trade policies. Although high protection on imports could increase the inconvenience of protectionism, the positive impact of projectionist measures (after controlling for endogeneity bias) is undetermined. We find that protectionist measures imposed by the respondent’s country do not significantly influence protectionism support in general. It remains unclear that our result is due to reverse causality or the fact that people are not aware of the real level of protectionism or are really not sensitive to this aspect. We have also tested how easy access to their exports reduces people’s support for restrictive measures on imports. We find that poorer access to international markets has a significant and positive impact on support for import protectionism. This demonstrates that exports are viewed as a counterweight to the removal of national restrictions.
Since individuals’ opinions towards trade policies do not only depend on noneconomic factors such as values and demographic characteristics but also on the labour market situation and macroeconomic contexts, recessions may increase protectionism pressures. Our study also shows that people are sensitive to the access granted by their trade partners to national exports and that pressures could therefore spread quickly from one country to another. It appears that the best way to overcome the pessimistic view about free trade is to increase skills. Indeed, more educated people are more likely to favour free trade wherever they live. Providing transparent information about trade restrictions, trade composition and the importance of export sectors and foreign markets might also reduce support for protectionism.
J. Milgram-Baleix gratefully acknowledges the financial support from SEJ 340 of the Junta de Andalucía and the MICINN project ECO2011-25737.