Master thesis
The Chinese import shock and economic nationalism:
The political and economic effects of the Chinese import shock
in the Netherlands in the period 1995-2017
University of Groningen
Faculty of Economics and Business
International Economics & Business
Deadline: 19
thof June 2018
Supervisor: dr. Robert Inklaar
Second corrector: dr. Anne Minasyan
Student: Demi Lissenberg
Student number: 3259080
The Chinese import shock and economic nationalism:
The political and economic effects of the Chinese import shock
in the Netherlands in the period 1995-2017
Abstract
I.
Introduction
It has long been argued that international trade is welfare improving. Basic trade theories suggest that international trade creates winners and losers. Owners of a country’s abundant factor are expected to gain from international trade, while owners of the less abundant factor lose. The gains of the winners are assumed to be substantial enough to offset the losses of the losers of international trade. Whether international trade is indeed Pareto-improving is nowadays questioned as manufacturing jobs are disappearing in Western society. This results in an uneven income distribution in the United States (U.S.) and in unemployment in Europe (Pelkmans, 2016; Autor, Dorn & Hanson, 2016). The losers of increased global trade call for compensation (Colantone & Stanig, 2017) or for more protectionism (Cerrato, Ruggieri, & Farrara, 2016).
At the same time, as global trade is peaking, Western democracies are witnessing a revitalization of nationalism. The economic side of nationalism proposes protectionism as a way to compensate the losers of globalization. Two major exhibits of the revitalization of nationalism is the Brexit referendum and the election of the American president Donald Trump. In Europe this trend of increasing nationalism has been linked to increasing support of radical right parties (Colantone & Stanig, 2017), such as National Front in France (Malgouyres, 2017). Radical right parties have a more extreme nationalistic, protectionist and nativist ideology. Economic globalization has fostered demand for protectionism, especially by the sectors hit by increased import competition and their employees (Cerrato, Ruggieri, & Farrara, 2016). The rise of radical right parties is a Europe-wide phenomenon. While extreme right parties have benefitted from increased import competition in Europe, protectionist left parties have not. As solely extreme right parties and not protectionist left parties have gained vote shares from increased import competition, consequently the Chinese import shock does not lead to political polarization in Europe (Colantone and Stanig, 2017).
effects and clustered standard errors. Furthermore the economic impact of the import shock is explored by studying the effect of increased import competition on manufacturing rewards and manufacturing employment. The change in log weekly rewards and the log change in employment volume are examined.
This study adds to existing literature as the effect of the import shock on Dutch referendums has not been previously examined. This could provide meaningful insights, especially when considering a possible ‘Nexit’ referendum in the future, where the winners-take-all. Moreover, the political landscape of the Netherlands makes it a particularly interesting country to study as the elections in the Netherlands are totally different from winner-takes-all contests, as the election of Donald Trump. Additionally, compared to the study of Colantone & Stanig (2017), this study takes a more in depth perspective when examining the Netherlands. Colantone & Stanig (2017) examine the impact of the Chinese import shock on political right parties in Western Europe. They pile the data of 15 European countries, including the Netherlands, to get an overall result for Western Europe. They divided the Netherlands into 4 areas when examining the effects of the import shock in the period 1995-2007. This study focusses solely on the Netherlands by examining 40 areas the Netherlands in the period 1995-2017, compared to Colantone & Stanig (2017) where all data of 15 European countries is piled and no separate result for the Netherlands is derived. This study uses 40 Dutch areas instead of the 4 areas proposed by Colantone & Stanig (2017) in order to compute a more area-precise import shock and get more exact results. Furthermore a longer time span is used in order to see if there is a long lasting political trend present in the Netherlands.
Moreover, the Netherlands has a low unemployment rate, low levels of inequality and a high minimal wage, compared to the rest of Europe and the U.S. It is very interesting to examine whether the import shock still has an effect on these economic features, considering that the Netherlands is not home to any large unemployment or inequality problems. Autor, Dorn and Hanson (2013) examine this in regards to the U.S. The U.S. is known to be the home of large income- and wealth inequality. It would be interesting to test if the Chinese shock has the same effects in a country with low inequality.
benefits protectionist left parties. Concluding, increased import competition does not lead to political polarization in the Netherlands. The fact that the import shock benefits extreme right- and hard skeptic parties could suggest that globalization might not be sustainable in the long run if the welfare gains brought my trade are not shared within the community. When nationalist parties become more and more popular, their protectionist and isolationist ideology might be a threat to the trade open world as we know it. Protectionist ideology expresses itself with tariffs and quotas to boost domestic industry, such as the recent steep import tariffs on steel and aluminum, implemented by president Trump. Appropriate redistribution polies need to be in place, compensating the ‘losers’ of globalization in order to limit protectionism and to keep the Netherlands trade open.
Furthermore this study suggests negative employment effects in the manufacturing sector as a result of the China shock. No significant effect of increased import competition on non-manufacturing employment has been established. These results suggests that the unemployment effects of the import shock are solely carried by the hit sector and not diffused among society. If labor was mobile between sectors, the laid-off workers of the manufacturing sector would have been absorbed by the non-manufacturing sector. Results suggests this is not the case in the Netherlands.
This study fails to find a significant association between import penetration and wages. An explanation for the insignificant effect of the import shock on wages is that the most productive workers retain their jobs in manufacturing, thus biasing the estimation against finding a reduction in manufacturing wages (Ebenstein, Harrison, McMillan, & Phillips, 2014). Another explanation is that manufacturing plants react to import competition by accelerating technological and organizational innovations that increase productivity, oppressing the reduction of wages (Bloom, Draca and van Reenen, 2009). Additionally, this insignificant finding is in line with literature suggesting that the results of increased import competition in Europe is unemployment, not a reduction in wages, as institutions in Europe protect the bottom tiers of the wage distribution (Pelkmans, 2016).
II. Literature review
a. Globalization and the China shock
Trade theory suggests that developing countries have a strong impact on labor markets in high wage countries due to their specialization in unskilled labor (Krugman, 2008). China acceded to the World Trade Organization (WTO) in 2001, which led to an enormous surge in trade that increased the country’s share of world manufacturing exports from 4.8% in 2000, to 15.1% in 2010 (Autor, Dorn, Hanson & Majlesi, 2016). In a relatively short period of time China has changed its closed, agricultural based economy into a leading, open, manufacturing economy (Colantone & Stanig 2017).
Several studies examining the China shock argue that there is a significant displacement of manufacturing activities in both the U.S. and the European Union (EU), particularly within labor intensive manufacturing activities (Autor, Dorn and Hanson, 2013; Bernard, Jensen, Schott, 2006; Bloom, Draca, Van Reenen, 2016; Khandelwal, 2010). More detailed, Acemoglu, Dorn, Hanson & Price (2016) find that the amount of job losses in the U.S. due to import competition from China is between 2 and 2.4 million. Import competition from China explains about a quarter of the aggregate decline in U.S. manufacturing employment (Autor, Dorn, Hanson, 2013).
of total U.S. exports to total imports from all countries, then there is a rise in net labor demand due to the growth in service exports. Their results would suggest that the job losses due to the Chinese import shock could be compensated by an increase of merchandise- and, most importantly, service exports to all countries.
wages are highly flexible and the decrease in demand for the less skilled lowered their wages. In Europe, where institutions protect the bottom tiers of the wage distribution, the decline in demand for less skilled workers resulted in unemployment. These different consequences of increased import competition can be seen in figure 1 and 2.
Figure 1: Unemployment as total % of total labor force, WorldBank (2018)
Figure 2: Income divisions according to national income standards in 2010, Pew Research Center (2017)
Moreover, the employment and wage effects of increased import competition depend on the categorization of the jobs (WTO, 2008). It is generally stated that routine jobs are more vulnerable to offshoring and automatization than non-routine jobs. These routine jobs are often categorized as medium-skilled. This could explain why researchers on globalization and labor markets moved away from the distinction between two types of workers: high- and low skilled,
0% 2% 4% 6% 8% 10% 12% 14% 19951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017
EU and U.S. unemployment rate
EU U.S. 14% 14% 13% 17% 17% 17% 18% 19% 22% 19% 24% 16% 80% 80% 79% 75% 75% 74% 72% 69% 67% 67% 64% 59% 7% 6% 8% 8% 8% 9% 10% 12% 11% 14% 13% 15% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Denmark Norway Netherlands Finland Luxembourg France Germany Ireland Italy United Kingdom Spain U.S.
Percentages of adult population in lower-, middle-, and upper income 2010
and include a group of medium skilled workers. Note that the middle- and low skilled categories are still considered low skilled in absolute terms (Forbes, 2001).
When adding a third, medium skilled category, studies suggest that international trade has been a contributing factor of job polarization in Western society. Job polarization refers to “a pattern of changes in the composition of employment whereby there is an increase in the share of employment in high skilled jobs, a decrease in the share of middle skilled jobs, and an increase in the share of low skilled jobs” (Coelli, Borland, 2016, p:1). This phenomenon suggests an increase in demand for high-skilled employees and low-skilled employees, while demand for middle-skilled employees decreases. This shifts employment into a U-shaped distribution (Cozzi & Impullitti, 2016). High-skilled professions are for example managerial, professional and technical occupation such as doctors and scientists (Autor, 2015). Middle-skilled professions are for instance office- and administrative support, production, craft and repair, operator and fabricator. These professions mainly include routine tasks, predominantly manufacturing, which are easily offshored to wage countries or automatized. The low-skilled professions often involve helping or assisting others, which are professions such as maids, waiters and truck drivers. These low-skilled occupations cannot be offshored. Most of the employees in these service occupations do not have a post-high school education. As the middle-skilled professions disappear, either due to offshoring of manufacturing activities to low-wage countries or due to automatization, the middle skilled workers relocate mainly to the low-skilled professions. This is due to the fact that these middle-skilled employees would need additional training or schooling in order to move to the high-skilled occupations, therefore they move to the low-skilled spectrum, for which they do not need additional schooling. Thus a result of the disappearance of the middle-skilled professions is the increase of the low-skilled labor force supply. As a consequence of this increase of the low-skilled labor supply, the wages of low-skilled occupations decrease. This would suggest that job polarization does not lead to wage polarization, as the wages of both low-skilled professions and medium-skilled professions decrease.
the benefits are diffused amongst the community, the losses of the firms and the loss of jobs determine the losers of international trade.
b. Economic voting theory
Classic economic voting theory suggest that voters punish the incumbent party for weak economic performances such as a high unemployment, high inflation and low GDP growth, and reward them for the opposite (Fair, 1978; Kramer, 1971; Duch & Stevenson, 2008). In regards to import competition, it has a strong influence on regional economic conditions, and can thus influence voting behavior. Voters in regions gaining from increased international trade are expected to reward the incumbent and voters in regions losing from global trade are expected to punish the incumbent. This is also known as the anti-incumbent effect. Jensen, Quinn and Weymouth (2017) provide strong evidence for the anti-incumbent effect in the 2016 U.S. presidential elections. Their research builds upon the fact that import competition in the manufacturing sector diminishes political support for incumbents. Their results suggest that there is a decrease in incumbent party vote shares in counties with a high amount of low-skilled manufacturing workers, and an increase in counties with large number of workers in high-skilled tradable goods and services.
Besides the anti-incumbent effect, there may be a polarization effect in place when elections are impacted by import competition. The polarization effect suggests that voters favor extremists instead of centrist politicians. An important aspect of the rise of polarization is that import competition is concentrated in specific geographical regions and sectors. Local labor employed in the manufacturing sector disproportionately bears the costs of import competition, which results in extreme political points of view (Acemoglu, Autor, Hanson, Price, 2016). Dippel, Gold & Heblich (2015) state that import competition leads to political radicalization, while exports lead to moderation. Looking at the U.S. again for example, the polarization effect can be seen in the 2016 presidential election. Trump’s key aspects in the presidential elections were the nativist, protectionist and conservative aspects of his campaign, such as the claim that American jobs fled to China and Mexico.
workers without a college degree to obtain a middle class way of life. Nowadays, these options have largely disappeared, resulting in an increasingly divided, polarized workforce with workers in low paid service jobs and high-wage professions (Autor & Dorn, 2013). The counties hit by greater Chinese import shocks are the same counties where the Republican presidential candidate gained more votes in 2016 (Cerrato, Ruggieri, & Farrara, 2016). The finding that counties experiencing greater import competition shift towards the Republican candidate in the 2016 presidential elections (Jensen, Quinn, & Weymouth, 2017), is a supporting result of the economic voting theory connecting adverse economic conditions to support for nationalists, nativists or extreme politicians (Autor, Dorn, Hanson, & Majlesi, 2016).
This phenomenon has not solely been seen in the U.S. Nationalism or support for extreme politicians can also be found in Europe; a stronger regional exposure to the China import shock determines an increase in support for nationalist, isolationist, and radical parties in Western Europe (Colantone & Stanig, 2017). Furthermore, they suggest that the Chinese import shock is a key structural determinant of the Brexit vote. There is a clear positive association between the strength of the import shock and support for the vote to leave the European Union. Additionally, Malgouyres (2017) states that in France there is evidence of a positive impact of import competition on voting behavior in favor of extreme right parties, which have more extreme nationalists and nativist ideologies. Dippel, Gold, Heblich (2015) come to the same conclusion when examining Germany. They state that extreme right parties respond significantly to trade integration in Germany. Extreme right parties gain votes with import competition and lose votes when export opportunities increase. It is suggested that import competition has negative effects on the labor market and state that where labor market responses are larger, political responses are too.
It could be questioned why the demand for protectionism has not been implemented by radical left parties. Indeed, radical left parties have also voiced points against trade integration (Hooghe, Marks, & Wilson, 2002; Halikiopoulou, Nanou, & Vasilopoulou, 2012). Left parties combine the closure of international trade with the promise of empowering a welfare state. Kriesi et al. (2012) and March and Mudde (2005) state that radical right parties have been more successful over the last decades than radical left parties. Radical right parties gain more from the increased demand for protectionism. This can be explained firstly because the renewed welfare state as promised by the radical left party needs to be financed. This is done by raising taxes, which might not be appealing to the middle-class. The middle-class is more attracted to the political views of the radical right parties. Second, Kriesi er al. (2012) state that the losers of international trade are less agitated by the political views of the right in regards to their cultural position. The left has a multicultural position. It has a reputation of humanist internationalism and therefore it might lack the credibility to propose exclusionary policies. Colantone & Stanig (2017, p:24) state that ‘districts that are more exposed to the Chinese import shock tilt either towards conservative Republicans or towards left-wing Democrats, thus leading to increased ideological distance. We do not detect a similar outcome in Western Europe over our period of analysis, due to the lack of success of protectionist-left bundles in response to the import shock.’
It is expected that the import shock favors extreme right parties, and not protectionist left parties, as previous studies have established a relationship between the import shock and the revitalization of extreme right parties in Europe. Left parties do not seem to benefit from increased import competition. Furthermore the political landscape of the Netherlands is particularly interesting as the Dutch population voted negatively in the European Union related referendums of 2005 and 2016.
Moreover the economic effects of increased import competition from China are examined. It is questioned whether import exposure has a significant effect on employment volume and rewards in the manufacturing sector and non-manufacturing sector. It is expected that the import shock has a negative effect on employment volume and no significant effect on rewards as literature suggest negative employment effects in Europe and negative wage effects in the U.S. and the Netherlands has a relatively high minimum wage. The Netherlands is an interesting country to study as it has relatively low unemployment rates compared to both the U.S.- and the European average (World Bank, 2018). As previous studies suggest that a negative result of the Chinese import shock in Europe is unemployment, it is interesting to examine whether the Chinese import shock indeed has a significant negative effect on employment in the Netherlands, despite the fact that unemployment rates have been relatively low over the two past decades.
It is important to examine this as Western politics have been shifting towards a protectionist direction, resulting in events such as Brexit and the election of Trump. It is important for the Dutch government to know if populist left or right parties benefit from increased import competition. Furthermore, it is important to explore the effects of increased import competition in a country with low inequality and low unemployment rates.
c. Political parties in the Netherlands
man’ from disadvantages of economic globalization (van der Waal, de Koster, 2017). Lijst Pim Fortuyn (LPF) was also a radical right party. LPF dissolved in 2003 after its leader, Pim Fortuyn, was murdered. An overview of all political parties, their abbreviations and the seat division in the elections of 1998-2017 is provided in the appendix table 1 and 2.
Furthermore, there are several Eurosceptic parties in the Netherlands. Euroscepticism is defined as ‘opposition to one of the two basic principles of European integration, namely the formation of a European free market and the sharing of national sovereignty’ (Vollaard & Boer, 2005, p:15-22). Eurosceptic parties can subsequently be divided into ‘hard sceptic’ parties, who oppose the basic principles and, for example, advocate withdrawal from the European Union. And ‘soft sceptic’ parties, who oppose further or less European integration in the form of the further sharing of sovereignty and the expansion of the European free market (Scszerbiak & Taggart, 2008).
Before 1991, The Staatkundig Gereformeerde Partij (SGP), the Gereformeerd Politiek Verbond (GPV) and the Reformatorische Politieke Federeatie (RPF) were against European integration due to the fact that they did not want to surrender the sovereignty given by God to the Netherlands to a supranational union that was dominated by Catholic and secular forces (Vollaard & Voerman, 2017). Later on, during the 1990’s and 2000’s (in which the GPV and RPF would dissolve in 2002), the SGP, GPV, RPF and the Christen Unie (CU) shifted from hard Euroscepticism to soft Euroscepticism. Besides these religious parties, the SP also was sceptic about European integration. The SP was considered hard skeptic in the period 1991-2005 and soft skeptic of 1991-2005 onwards. The SP had the opinion that the liberal market order of the European Union served only the interests of business.
rejection of the European Constitution Treaty in 2005, the Eurosceptic parties found proof that there was no support for European integration.
Table 3: Viewpoints on European integration, Vollaard, Voerman (2017).
Furthermore, until 2009, differences in viewpoints about European integration did not yet leave a strong mark on election campaigns, coalition building or on parliamentary decision-making.
In the subsequent campaign for the early parliamentary elections of 2012, European integration was for the first time a central theme in the debates between the parties. The electorate of CDA, PvdA and VVD appeared more or less equally divided on whether European integration should go further or not. The supporters of GL and D66 were generally for more European integration, while the voters of SP, CU, PvdD, SGP, 50+ were softly skeptic about it. 50+ was not against the European Union or the Euro, but against the Eurobonds and are therefore still considered as soft skeptic. Especially the PVV felt that European integration had already gone too far. After the 2012 elections, the majority of the Dutch voters voted against the Ukraine Association Agreement in 2016.
80’s After the Maastricht treaty (1991)
After the referendum of 2005
III. Data and methods
This research examines the impact of the Chinese import shock on voting behavior in the Netherlands in the period 1995-2017. Colantone and Stanig (2017) is followed.
1. Electoral outcome
rt= β
1Import Shock
rt+ Z
rt+ ε
rtElectoral outcomert is the percentage that voted for a soft skeptic party, a hard skeptic party or the right political parties in the Netherlands (PVV, LPF), and voted unfavorable in the referendums of 2005 and 2016. The import shockrt is the growth in Chinese imports over the two years before the election, which is held in year t. Zt is a vector of COROP level controls. This includes age, the percentage of males, and a set of variables indicating different levels of educational attainment.
Furthermore, the economic impact of the import shock is also examined for the Netherlands 1995-2017. The effect of the import shock on manufacturing rewards and manufacturing employment is examined. Autor, Dorn and Hanson (2013) is followed.
2.
LOGRewards
rt= β
1Import Shock
rt+ Z
rt+ ε
rt3.
LOGEmployment
rt= β
1Import Shock
rt+ Z
rt+ ε
rtLOGRewardsrt is the change in log weekly rewards. LOGEmploymentrt is the log change in employment volume. Zt is a vector of COROP level controlling for different levels of educational attainment. Logarithms are taken in order to transform the data into a normal distribution.
a. The Chinese import shock
Several studies have examined the link between the Chinese import shock and the labor market at the regional level. It is suggested that regions are more vulnerable to the Chinese import shock because of their sectoral specialization. Regions that are more vulnerable to the import shock are expected to face employment losses and lower wages as import competition increases. On a bilateral basis, the extent of this effect depends on the fact that China’s demand for foreign goods does not compensate the displacement induced by its exports, which is realistic given the rising trade surplus China has run over time, particularly after entering the WTO (figure 3). On a global basis, given the positive trade balance of the Netherlands over time (figure 4), the extent of the employment losses and lower wages depends on the unequal distribution of the costs of international trade.
Figure 3: Import, export and trade balance of the Netherlands with China 1995-2017, CBS (2018)
Figure 4: Import, export and trade balance of the Netherlands 1996-2017, CBS (2018)
-40000 -30000 -20000 -10000 0 10000 20000 30000 40000 19951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017
Dutch trade balance with China (million euro's)
Imports Exports Trade balance
0 100000 200000 300000 400000 500000 1996199719981999200020012002200320042005200620072008200920102011201220132014201520162017
Dutch trade balance (million euro's)
Consequently, the trend of a decline in employed persons in the Netherlands in the manufacturing industry can be seen in the following figure.
Figure 5: Full time employed persons in manufacturing industry, CBS (2018)
Autor, Dorn and Hanson (2013) and Colantone & Stanig (2017) derive an empirical measure of regional exposure to the China import shock from a supply side perspective. Autor, Dorn and Hanson (2013) and Colantone & Stanig (2017) employ the same empirical approach, which is also used in this research. The trade shock at the regional level is measured as follows:
4.
is the change in imports to the Netherlands from China (in million euro’s current prices) over the past two years, in industry k. This is normalized by the total number of workers in the same industry in the Netherlands at the beginning of the sample period, . In order to back out the region specific trade shocks, the weighted sum of the change in imports per worker across industries is taken, where the weights capture the relative importance of each industry in a given region. Specifically, the weights are defined as the ratio of the number of workers in region i and industry k, , over the total number of workers in the region
, both measured at the beginning of the sample period.
The intuitive interpretation of this measurement is that: for given changes in nation level imports per worker ( ), the Chinese import shock will be stronger in those regions in which a larger share of employees was originally occupied in
600 650 700 750 800 850 900 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Full time employed persons (x1000) in the manufacturing sector
industries observing larger subsequent increases in imports from China. Cross regional variation could arise from two sources. Firstly, larger shocks are ascribed to regions in which more workers were originally employed in the manufacturing sector. However, for a given overall share of manufacturing employees, the shock will be stronger for regions in which more employees were occupied in industries for which Chinese imports have increased the most e.g. textile or electronics.
Industrial specialization in measured in 1995, before the emergence of China as a global manufacturing player. Thereafter the import growth between 1996 and 2017 is examined. This time period reassures that the effects found in their research are manifestations of long-term processes taken place, rather than consequences of a singular shock like the global financial meltdown of 2008. Colantone & Stanig (2017) measure industrialization in 1989, however unfortunately there is no specialized import data available as off 1996, therefore industrial specialization is measured in 1995. This works perfectly, as the Chinese import then began to grow, which can be seen in figure 3. Import Shock is the growth in imports from China, computed over the past two years before the election, which is held in year t.
The Centraal Bureau voor de Statistiek (CBS) provides COROP-level (Coordination Commission Regional Research Programme) regional data on the labor inputs per industrial specialization within the manufacturing sector. COROP is a classification of the Netherlands in 40 areas, in which the commuting flows have served as a basis. For the comparability of figures over several years, it is important to note that the COROP areas do not change over time. Furthermore, the borders of the COROP region follow (almost) all provincial borders. Every COROP area has a central core (city) with a surrounding catchment area.
Manufacture of basic metals 8) Manufacturing of metal production, machinery and equipment 9) Electrical and optical equipment 10) Manufacture of transport equipment 11) Manufacturing nowhere else specified.
b. Political data
De Kiesraad and the Ministerie van Binnenlandse Zaken en Koningkrijksrelaties (the Dutch government) provide a database for all elections and referendums since 1848. For each municipality there is data on vote shares at the party level. The municipalities are further categorized by 40 COROP areas based on CBS regional municipality listing (appendix table 5), which makes the political data consistent with the data of the import shock. The elections of 1998, 2002, 2003, 2006, 2010, 2012 and 2017, the referendum of 2005 and the referendum of 2016 are taken into account.
Again, following Colantone & Stanig (2017), there are/were two extreme right parties active in the Netherlands in the period 1995-2017, namely the LPF and PVV.
Furthermore, the viewpoint on European integration can be seen as a good indicator to examine whether a party is pro international trade or more protectionist and nationalistic and thus skeptic about European integration. The SP had a hard skeptic viewpoint in the period 1991-2005, which turned in to a softer skeptic viewpoint after the referendum of 2005. Moreover, the PVV had a hard septic point of view after the referendum of 2005. Accompanied by the FvD in 2017 (table 3).
c. Control variables
d. Employment and wage effects
IV. Results and analysis
a. DescriptiveTable 4 displays the core descriptive in regards to the elections of 1998, 2002, 2003, 2006, 2010, 2012 and 2017. Hard skeptic and soft skeptic parties have gained total vote shares over the period (figure 6). The extreme right parties PVV and LPF have also gained vote shares over the period. In 1998 there were no extreme right parties in the Netherlands and in 2017 the PVV totaled 13,07% of the overall vote share. The strong decline in vote shares of the LPF in 2003 could be attributed to the murder of Pim Fortuyn. Furthermore it is worth mentioning the noticeable increase in PVV vote shares in 2010. This could be ascribed to the strong increase of imports from China, which can be seen in figure 3. It is worth noting that the Chinese import shock calculated in this study is also the largest in 2010.
The total overview of the import shock per COROP area per year, as well as the (combined) share of votes, can be found in the appendix table 6 and 7. The average vote shares and additional descriptive data per COROP region for the elections and referendums can also be found in the appendix table 8, 9 and 10, as well as the minimum, maximum and mean of the import shock.
PVV/LPF Hard skeptic Soft skeptic Import shock
1998 0 .0381 .0618 .2840 2002 .1573 .0512 .2067 .5059 2003 .0541 .0561 .0926 .4255 2006 .0570 .0550 .1873 1.5655 2010 .1511 .1511 .1662 1.6081 2012 .0980 .0980 .1889 .5293 2017 .1307 .1488 .2191 .9737
Table 4: Mean PVV/LPF, hard skeptic parties, soft skeptic parties and the import shock (in million euro’s) 1998-2017
Figure 6: Mean PVV/LPF, hard skeptic- and soft skeptic parties 1998-2017
0% 5% 10% 15% 20% 1998 2002 2003 2006 2010 2012 2017
Average vote shares by election
b. The Chinese import shock.
The main results of the effect of the Chinese import shock on voting behavior in the Netherlands in the period 1995-2017 can be seen in table 11. The Chinese import shock has a positive, significant effect on voting in favor of the PVV/LPF and the hard skeptic parties in the Netherlands. The coefficient on the Chinese import shock is positive and statistically significant, indicating that elections tilt in a more protectionist direction when exposed to a higher level of Chinese import competition.
PVV/LPF Hard Soft Against Import shock .0208005*** (.0037719) .0182258*** (.0035622) -.1595594 (.1821842) -.0031987 (.0066808) Observations 200 200 200 80 Number of groups 40 40 40 40 R2 within .1971 .6660 .0306 .1849 R2 between .2986 .1606 .0007 .1591 R2 overall .1348 .2589 .0022 .0864
Table 11: Effect of the import shock on the PVV/LPF, hard- and soft skeptic parties and voting unfavorable in the referendums of 2005 and 2016, estimating with fixed effects and clustered standard errors, * p<.1, ** p<.05, *** p<.01.
Putting this more in perspective, when comparing the five COROP regions with the largest import shock to the five COROP regions with the smallest import shock, results suggest that the import shock only has a positive significant effect on the vote shares of the PVV/LPF and hard skeptic parties in the five COROP regions with the largest import shocks. This implies that a million euro increase of the Chinese import shock results in a 5,8640% increase in support of the PVV/LPF and 3,5347% in favor of hard skeptic parties. In regards to the five COROP regions with the smallest import shock, there is no significant effect of the import shock on voting in favor of the PVV/LPF or hard skeptic parties.
Table 12: The effect of the import shock on the vote shares of the PVV/LPF and hard skeptic parties of the five COROP regions with the largest import shock: Midden-Limburg, Zuidwest-Drenthe, Zuidoost-Zuid-Holland, Noord-Overijssel, Zuidoost-Noord-Brabant, and the five COROP regions with the smallest import shock: Ijmond, Oost-Zuid-Holland, Delfzijl, Zeeuwsch-Vlaanderen, Zuidwest-Overijssel. Estimating with fixed effects and clustered standard errors, * p<.1, ** p<.05, *** p<.01.
Focusing more on these previous results, the significant and positive coefficients of the PVV/LPF and hard skeptic parties are relatively similar. Examining the hard skeptic parties further, it becomes clear that the import shock has had a positive significant effect on the vote shares of the PVV in the period it has been active (2006-2017). Results imply that a million euro increase of the import shock increases the PVV vote share in the period 2006-2017 with 1,5056%. The PVV has always been very skeptic towards European integration and results suggest the party has benefited from the Chinese import shock. In regards to the SP, which has been very skeptic towards European integration in the period 1991-2005, there is no significant relationship between the import shock and voting in favor of the SP found in this period. Nor has the import shock benefitted the SP in the period 2006-2017, where it did benefit the PVV, or in the entire sample period 1998-2017. The lack of success in response to the import shock of the SP, a protectionist left party, is in line with previous studies, which established a significant positive association between the import shock and voting in favor of extreme right parties and not in favor of left parties.
PVV (2006-2017) PVV (1998-2017) SP (1998-2003) SP (2006-2017) SP (1998-2017) Import shock .015056*** (.0040205) -9.6896 (7.0803) .0142479 (.0146425) -.01105 (.0131671) .0012587 (.008812) Observations 120 200 80 120 200 Number of groups 40 40 40 40 40 R2 within .7320 .6187 .2926 .2115 .2529 R2 between .0635 .0001 .0100 .0900 .0001 R2 overall .1671 .2997 .0055 .0561 .0534
c. Employment- and wage effects
Following Autor, Dorn and Hanson (2013), in table 14, the employment effects are explored, separately for employees working in the manufacturing and non-manufacturing sector. In table 14 it is confirmed that import competition leads to a reduction in employment in the manufacturing sector and has no significant effect on non-manufacturing employment. A significant negative effect of the import shock on employment volume in the manufacturing sector has been established. Results suggest that a million euro increase of the import shock leads to a .2014 log point reduction of overall manufacturing employment. The point estimates are relatively comparable when controlling for college (p=.092) and non-college (p=.03). When separating this effect further by controlling for low-, middle-, and high education, results suggest that the Chinese import shock does not have an effect on the high educated in the manufacturing sector, but there is a significant negative effect on the low-, and middle educated.
In table 15, the wage effects are examined, again separately for workers employed in manufacturing and non-manufacturing. Although import competition reduced manufacturing employment, table 15 suggests that there is no significant effect on manufacturing and non-manufacturing wages. These results are in line with other industry level studies such as Ebenstein, Harrison, McMillan & Phillips (2010) and Edwards and Lawrence (2010), whom find no negative wage effects of imports on U.S. employees in import exposed manufacturing industries. An explanation for the insignificant effect of the import shock on wages is that the most productive workers retain their jobs in manufacturing, thus biasing the estimates against finding a reduction in manufacturing wages. Another explanation, suggested by Bloom, Draca and van Reenen (2009), is that manufacturing plants react to import competition by accelerating technological and organizational innovations that increase productivity, oppressing the reduction of wages.
Manufacturing; Log change in employment volume Non-manufacturing; Log change in employment volume Import shock Observations Number of groups R2 within R2 between R2 overall
All Non-college College
-.2013752** (.1038456) -.1755974*** (.0779567) -.1746801* (.1012138) 120 160 120 40 40 40 0.0550 0.0405 0.0460 0.1487 0.0008 0.1529 0.0245 0.0193 0.0313
All Non-college College
.241893 (.2008286) .2253556 (.1369426) .239533 (.1937232) 120 160 120 40 40 40 0.1979 0.0668 0.1979 0.2563 0.0438 0.0042 0.1210 0.0020 0.0575
Table 14: The effect of the import shock on employment volume, estimating with fixed effects and clustered standard errors, * p<.1, ** p<.05, *** p<.01, **** p<.001.
Manufacturing; Log change in employment volume Non-manufacturing; Log change in employment volume
Import shock Observations Number of groups R2 within R2 between R2 overall
All Low Middle High
-.2013752** (.1038456) -.175597*** (.0779567) -.2168793** (.0972188) -.1419492 (.092239) 120 160 120 160 40 40 40 40 0.0550 0.0405 0.0361 0.0437 0.1487 0.0008 0.1583 0.1357 0.0245 0.0193 0.0272 0.0022
All Low Middle High
Manufacturing; Change in log weekly wages Non-manufacturing; Change in log weekly wages Import shock Observations Number of groups R2 within R2 between R2 overall
All Low Middle High
-.1347094 (.1054215) -.0965681 (.0805454) -.1218292 (.105882) -.0766108 (.0967166) 120 160 120 160 40 40 40 40 0.0315 0.0151 0.0106 0.0157 0.0406 0.1359 0.0516 0.0449 0.0039 0.0065 0.0051 0.0052
All Low Middle High
-.0385448 (.0515979) .0131931 (.0648385) -.0075355 (.0796511) -.0118061 (.0740205) 120 160 120 160 40 40 40 40 0.0712 0.0038 0.0177 0.0006 0.0025 0.0522 0.0199 0.0041 0.1210 0.0264 0.0119 0.0022
Manufacturing; Change in log weekly wages Non-manufacturing; Change in log weekly wages Import shock Observations Number of groups R2 within R2 between R2 overall
All Non-college College
-.1347094 (.1054215) -.0965681 (.0805454) -.0973022 (.1084485) 120 160 120 40 40 40 0.0315 0.0151 0.0139 0.0406 0.1359 0.0217 0.0039 0.0065 0.0033
All Non-college College
-.0385448 (.0515979) .0131931 (.0648385) -.057285 (.0476752) 120 160 120 40 40 40 0.0712 0.0038 0.0582 0.0025 0.0522 0.0001 0.1210 0.0264 0.0035
IV.
Limitations
There are several limitations to this study. First, the insignificant result of the import shock on voting behavior in the referendums is unexplained. Second, this study fails to find a reason why the PVV vote share dropped in 2012. Third, there are several data limitations: 1) there is only data available for the MBO and FAVO attainments for four elections. Education data can therefore also not be lagged ten years, following Autor, Dorn and Hanson (2013), 2) there is no wage data available per COROP region per sector, only reward data, which includes additional features such as bonuses, overpay and holiday pay.
Moreover, it is important to mention to what extent this study follows Colantone & Stanig (2017) and Autor, Dorn & Hanson (2013). Colantone and Stanig (2017) is followed for studying the effects of the import shock on voting behavior. The same approach is used when calculating the import shock. Moreover the LPF and PVV are both listed as extreme right parties in this research as well as theirs. They also use viewpoints on European integration when reflecting on political parties. However, Colantone & Stanig (2017) extend their categorization of political parties further. They score parties also on nationalism and national autarky. They do this by creating three main scores reflecting nationalism and isolationism ideology. The first is a basic score of nationalism based on claims about the national way of life, traditional morality, law and order, and multiculturalism. The second is a specific score of net autarky, which includes claims about protectionism, internationalism, and the European Union. The third is a more comprehensive score of nationalist autarchy, which combines aspects of score 1 and 2 and includes also claims about human rights, democracy, and constitutionalism. This study does not score parties based on their nationalist and national autarky ideology, just on their viewpoint on European integration.
feasible in regards to the Netherlands. Specialized import data per COROP region is not available as of 1995.
V.
Conclusion and recommendations
The world has witnessed an increase in international trade between Western, high wage economies and low wage countries. The biggest rising player is China. China has evolved into a great economic power and this has brought about a shift in patterns of world trade. The strong and rapid growth of import competition can be seen in the industrialized world, for example in the Netherlands. This phenomenon can increasingly be seen since 1995 in the Netherlands, but has been strongly increasing since 2001, which is the year in which China became a WTO member.
This study provides evidence supporting the claim that Chinese import competition caused a rise in support for extreme right parties and hard skeptic parties in the Netherlands. There is no significant association established between the import shock and protectionist left parties. This suggests that import competition does not lead to political polarization, but only to the support of extreme right- and hard skeptic parties. The fact that the import shock benefits extreme right and hard skeptic parties could suggest that globalization in regards to free trade might not be sustainable in the long run if the welfare gains brought my trade are not shared within society. Appropriate redistribution polies need to be in place in order to compensate the ‘losers’ of globalization. When nationalist parties become more and more popular, their protectionist and isolationist ideology might be a threat to the trade open world as we know it. This could be an important lesson for the Dutch parliament.
non-manufacturing employment. Thus laid-off workers in the non-manufacturing sector are not absorbed by the non-manufacturing industry.
There is no significant effect of the import shock on wages in the Netherlands. Possible explanations for this result are that trade increases productivity, suppressing the reduction of wages. Moreover, institutions protect the bottom tiers of the wage distribution, again suppressing a decrease of wages.
Thus the import shock negatively effects manufacturing employment, but has no effect on wages. This is in line with previous studies suggesting that the import shock puts downward pressure on low-skilled wages. This results in an increases of income inequality in the U.S., and on the flip side, reduces employment in Europe. It should be noted that the Netherlands has a relatively low unemployment rate, both compared to the U.S. and the European average. However, the import shock still has a significant effect on employment in the manufacturing sector. By letting the wages fluctuate more freely, the reduction of manufacturing employment as a result of the import shock could be limited. However, inequality would rise. Thus by reducing one problem, another would arise.
fee during the first two years of their studies. More research should be conducted as to why the laid-off workers are not absorbed by the non-manufacturing sector in the Netherlands.
While this backlash against globalization is one of the key determinants of the rise of the popularity of extreme right parties in the Western world (Cerrato, Ruggieri, & Farrara, 2016), there are more aspects to be considered such as skill biased technological change and supply factors such as migration and the increased labor force participation of women.
Appendix
Party Dutch party name English party name VVD Volkspartij voor Vrijheid en
Democratie
People’s Party for Freedom and Democracy
PvdA Partij van de Arbeid Labour Party PVV Partij voor de Vrijheid Party for Freedom
CDA Christen-Democratisch Appèl Christian Democratic Appeal SP Socialistische Partij Socialist Party
GL GroenLinks GreenLeft
CU ChristenUnie Christian Union D66 Democraten 66 Democrats 66 PvdD Partij voor de Dieren Party for the animals SGP Staatkundig Gereformeerde Partij Reformed Political Party
50+ 50PLUS 50 Plus
Denk Denk Denk
FvD Forum voor Democratie Forum for Democracy
Table 2: Seats 1998-2017, Rijksoverheid 2018 Party 1998 2002 2003 2006 2010 2012 2017 VVD 38 24 28 22 31 41 33 PvdA 45 23 42 33 30 38 9 PVV - - - 9 24 15 20 CDA 29 43 44 41 21 13 19 SP 5 9 9 25 15 15 14 GL 11 10 8 7 10 4 14 CU - 4 3 6 5 5 5 D66 14 7 6 3 10 12 19 PvdD - - - 2 2 2 5 SGP 3 2 2 2 2 3 3 50+ - - - 2 4 Denk - - - 3 FvD - - - 2
COROP region Municipalities
Noord-Limburg Beesel, Gennep, Horst aan de Maas, Mook en Middelaar, Peel en Maas, Venlo, Bergen, Venray, Arcen en Velden, Helden, Kessel, Maasbree, Meerlo-Wanssum, Meijel, Sevenum
Zuid-Limburg Brunssum, Eijsden, Margraten, Stein, Beek, Gulpen-Wittem, Heerlen, Kerkrade, Landgraaf, Maastricht, Meerssen, Nuth, Onderbanken, Schinnen, Simpelveld, Sittard-Geleen, Vaals, Valkenburg aan de Geul, Voerendaal Midden-Limburg Echt-Susteren, Leudal, Maasgouw, Nederweert, Roerdalen, Roermond, Weert,
Ambt Montfort, Haelen, Heel, Heythuysen, Hunsel, Maasbracht, Roggel en Neer, Swalmen, Thorn
Flevoland Almere, Dronten, Lelystad, Noordoostpolder, Urk, Wieringermeer, Zeewolde
Zuidoost-Noord-Brabant
Asten, Bergeijk, Best, Bladel, Cranendonch, Deurne, Eersel, Eindhoven, Geldrop-Mierlo, Gemert-Bakel, Heeze-Leende, Helmond, Laarbeek, Nuenen- Gerwen- en Nederwetten, Oirschot, Reusel-De Mierden, Someren, Son en Breugel, Valkenswaard, Veldhoven, Waalre
Noordoost-Noord-Brabant
Boekel, Bernheze, Lith, Maasdonk, Schijndel, Sint-Oedenrode, Veghel, Boxmeer, Boxtel, Cuijk, Grave, Haaren, Heusden, Landerd, Mill en Sint Hubert, Oss, ’S-Hertogenbosch, Sint Anthonis, Sint-Michielgestel, Uden, Vught
Middennoord-Brabant
Aalburg, Alphen-Chaam, Baarle-Nassau, Dongen, Gilze en Rijen, Goirle, Hilvarenbeek, Loon op Zand, Oisterwijk, Tilburg, Waalwijk, Werkendam, Woudrichem
Westnoord-Brabant Zeist, Apeldoorn, Barneveld, Ede, Elburg, Epe, Ermelo, Hardewijk, Hattem, Heerde, Nijkerk, Nunspeet, Oldebroek, Putten, Scherpenzeel, Voorst, Wageningen, Bergem op Zoom, Breda, Drimmelen, Etten-Leur, Geertruidenberg, Halderberge, Moerdijk, Oosterhout, Roosendaal, Rucphen, Steenbergen, Woensdrecht, Zundert
Overig Zeeland Borsele, Goed, Kapelle, Middelburg, Noord-Beveland, Reimerswaal, Schouwen-Duiveland, Tholen, Veere, Vlissingen
Zeeuwsch-Vlaanderen
Hulst, Sluis, Terneuzen
Zuidoost-Zuid-Holland
Alblasserdam, Dordrecht, Giessenlanden, Gorinchem, Hardinxveld-Giessendam, Hendrik-Ido-Ambacht, Leerdam, Papendrecht, Sliedrecht, Zederik, Zwijndrecht, Vlist, Schoonhoven, Nieuw-Lekkerland, Liesveld, Graafstroom
Strijen, Vlaardingen, Westvoorne, Zuidplas, Bergschenkhoek, Berkel en Rodenrijs, Bleiswijk, Briefstemmen, Rozenburg, ’S-Gravendeel, Zevenhuizen-Moerkapelle
Oost-Zuid-Holland Alphen aan den Rijn, Gouda, Bodegraven, Bergambacht, Boskoop, Nederlek, Reeuwijk, Nieuwkoop, Waddinxveen, Liemeer, Moordrecht, Nieuwerkerk aan den IJssel, Ter Aar
Delft en Westland Delft, Midden-Delfland, Westland Agglomeratie
'S-Gravenhage
Leidschendam-Voorburg, Pijnacher-Nootdorp, Wassenaar, Rijswijk, ‘S-Gravenhage, Zoetermeer
Agglomeratie Leiden en Bollestreek
Hillegom, Kaag en Braassem, Katwijk, Leiden, Leiderdorp, Rijnwoude, Lisse, Noordwijk, Noordwijkerhout, Oegstgeest, Teylingen, Voorschoten, Zoeterwoude, Jacobswoude
Het Gooi en Vechtstreek
Blaricum, Bussum, Hilversum, Huizen, Naarden, Muiden, Laren, Weesp, Wijdermeren
Groot-Amsterdam Aalsmeer, Amstelveen, Amsterdam, Beemster, Diemen, Graft-De Rijp, Zeevang, Edam-Volendam, Haarlemmermeer, Landsmeer, Oostzaan, Ouder-Amstel, Purmerend, Uithoorn, Waterland
Zaanstreek Wormerland, Zaanstad Agglomeratie
Haarlem
Bloemendaal, Haarlem, Haarlemmerliede en Spaarnwoude, Heemstede, Zandvoort, Bennebroek
Ijmond Beverwijk, Castricum, Heemskerk, Uitgeest, Velsen
Alkmaar Alkmaar, Bergen, Heerhugowaard, Heiloo, Schermer, Langedijk Kop van
Noord-Holland
Andijk, Anna Paulowna, Den Helder, Harenkarspel, Drechterland, Enkhuizen, Hoorn, Zijpe, Wervershoof, Wieringen, Niedorp, Koggenland, Medemblik, Opmeer, Schagen, Stede Broec, Texel, Noorder-Koggenland, Obdam, Wester-Koggenland, Wognum, Alkemade
Utrecht Amersfoort, Baarn, Bunnik, Abcoude, Breukelen, Maarssen, Utrecht, Bunschoten, De Bilt, De Ronde Venen, Eemnes, Houten, Ijsselstein, Leusden, Lopik, Montfoort, Nieuwegein, Oudewater, Renswoude, Rhenen, Soest, Utrechtse Heuvelrug, Veenendaal, Vianen, Wijk bij Duurstede, Woerden, Woudenberg, Zeist
Zuidwest-Gelderland
Buren, Culemborg, Geldermalsen, Lingewaal, Maasdriel, Neder-Betuwe, Neerijnen, Tiel, West Maas en Waal, Zaltbommel
Agglomeratie Arnhem/Nijmegen
Arnhem, Beuningen, Doesburg, Druten, Duiven, Groesbeek, Millingen aan de Rijn, Rijnwaarden, Heumen, Lingewaard, Nijmegen, Overbetuwe, Renkum, Rheden, Rozendaal, Westervoort, Wijchen, Zevenaar
Veluwe Apeldoorn, Barneveld, Ede, Elburg, Epe, Ermelo, Harderwijk, Hattem, Heerde, Loenen, Nijkerk, Nunspeet, Oldebroek, Putten, Scherpenzeel, Voorst, Wageningen
Twente Almelo, Borne, Dinkelland, Enschede, Haaksbergen, Hellendoorn, Hengelo, Hof van Twente, Losser, Oldenzaal, Rijssen-Holten, Ubbergen, Twenterand, Wierden
Zuidwest-Overijssel Deventer, Olst-Wijhe, Raalte
Noord-Overijssel Dalfsen, Hardenberg, Kampen, Ommen, Staphorst, Steenwijkerland, Zwartewaterland, Zwolle
Zuidwest-Drenthe De Wolden, Hoogeveen, Meppel, Westerveld Zuidoost-Drenthe Borger-Odoorn, Coevorden, Emmen
Noord-Drenthe Aa en Hunze, Assen, Midden-Drenthe, Noordenveld, Tynaarlo
Zuidoost-Friesland Heerenveen, Ooststellingswerf, Opsterland, Smallingerland, Weststellingwerf Zuidwest-Friesland Bolsward, Nijenfurd, Skarsterlan, Sneek, Wanseradiel, Wymbritseradiel,
Gaasterlan-Sleat, Boarnsterhim
Noord-Friesland Achtkarspelen, Ameland, Dantumadiel, Dongeradeel, Ferwerderadiel, Franekeradeel, Het Bildt, Leeuwarderadeel, Lemsterland, Littenseradiel, Menaldumadeel, Harlingen, Kollumerland en Nieuwkruisland, Leeuwarden, Schiermonnikoog, Terschelling, Tytsjerksteradiel, Vlieland
Overig-Groningen Bedum, De Marne, Eemsmond, Grootegast, Haren, Leek, Marum, Ten Boer, Winsum, Zuidhorn, Groningen, Menterwolde, Hoogezand-Sappermeer Delfzijl e.o. Appingedam, Delfzijl, Loppersum, Slochteren, Winschoten, Slochteren,
Scheemda, Reiderland
Oost-Groningen Oldambt, Pekela, Bellingwedde, Vlagtwedde, Stadskanaal, Veendam
COROP region 1998 2002 2003 REF 2005 2006 2010 2012 REF 2016 2017 Noord-Limburg .2626 .6422 .6250 1.7613 1.4897 1.9143 .7183 -.5423 .95819 Zuid-Limburg .385610 .7536 .73349 2.4506 2.2652 2.47339 .78168 -.8035 1.379810 Midden-Limburg .81791 1.76211 1.74181 6.08081 5.65051 5.30851 1.19983 -2.6139 2.33192 Flevoland .1537 .2627 .2570 .9929 .9767 .8928 .2245 -.3770 .5090 Zuidoost-Noord-Brabant .43097 1.13634 1.08104 3.00618 2.39699 3.27944 1.20772 -1.0090 1.51388 Noordoost-Noord-Brabant .1691 .2545 .2428 .9010 .8884 .9694 .3506 -.2108 .6826 Middennoord-Brabant .2642 .4154 .2976 1.5318 1.3266 1.3469 .4440 -.4149 .9194 Westnoord-Brabant .42809 .91677 .75368 2.97549 2.45178 2.62937 .77029 -1.0836 1.3416 Overig Zeeland .46716 .83808 .714110 3.05557 2.82056 2.51208 .6756 -1.0940 1.46639 Zeeuwsch-Vlaanderen .3569 .4970 .0385 1.4067 .6319 1.4292 .95395 .22153 1.67025 Zuidoost-Zuid-Holland .60634 1.29163 1.18083 4.60863 4.16033 3.71043 .741410 -2.0360 1.59857 Groot-Rijnmond .2396 .4354 .3884 1.5848 1.4649 1.3756 .3484 -.6006 .7649 Oost-Zuid-Holland .9509 .1186 .0530 .4282 .3278 .4561 .2283 .01028 .4399 Delft en Westland .1317 .1549 .1400 .5158 .5508 .6775 .3080 -.04039 .6318 Agglomeratie 'S-Gravenhage .8526 .1526 .1417 .5656 .5465 .4740 .1229 -.2177 .2672 Agglomeratie Leiden en Bollestreek .2567 .4489 .4411 1.7321 1.7058 1.4942 .3229 -.7025 .7981 Het Gooi en Vechtstreek .2258 .4754 .2397 1.0233 .5754 .9873 .80667 .11405 .9743
Groot-Amsterdam .2491 .5089 .5012 1.8877 1.7937 1.5387 .2805 -.8640 .6566 Zaanstreek .1558 .2134 .1013 .7533 .5734 .7488 .3466 -.060110 .6693
Agglomeratie Haarlem .1036 .1371 .0603 .4555 .3133 .5149 .3070 .08436 .5082
Ijmond .3244 .6448 -.3552 1.2407 -.5376 .4348 1.11454 .62341 1.3490
Veluwe .1366 .1817 .1735 .7428 .7665 .7215 .2344 -.1858 .52951 Twente .1465 .3052 .1691 .7181 .3500 .9008 .5216 .03087 .6762 Zuidwest-Overijssel .1196 .0328 .0151 .3511 .4867 .3733 .2822 .18974 .6178 Noord-Overijssel .53685 .97316 .87075 3.62484 3.40184 2.97646 .7062 -1.4140 1.61106 Zuidwest-Drenthe .71532 1.54412 1.53462 5.57212 5.23462 4.55222 .87406 -2.5126 1.84543 Zuidoost-Drenthe .3282 .1833 .1378 .9326 1.2223 1.2672 .7219 .27032 1.69224 Noord-Drenthe .0879 .2021 .1902 .5164 .4544 .5722 .2737 -.1024 .3558 Zuidoost-Friesland .3513 .785510 .77017 2.531210 2.316710 2.3003 .6401 -1.0061 1.0619 Zuidwest-Friesland .42898 .82399 .80816 3.17556 3.11545 2.426310 .4641 -1.3848 1.1108 Noord-Friesland .2451 .4671 .4588 1.7705 1.7232 1.4325 .3164 -.7141 .7010 Overig-Groningen .1831 .3454 .3098 1.2381 1.1527 1.0413 .2877 -.4432 .5764 Delfzijl e.o. .63113 1.02505 .5608 3.31005 2.48557 3.03195 1.33251 -.5661 2.49021 Oost-Groningen .1878 .4543 .4478 1.3468 1.1458 1.4199 .4909 -.3992 .6774
Agglomeratie Haarlem PVV, LPF Hard Soft - 17,93% 5,42% 4,71% 12,49% 7,78% 9,83% Against 52,36% 57,05% 2,09% 5,31% 5,01% 4,57% 12,49% 7,78% 12,01% 1,82% 18,85% 6,22% 15,24% 9,11% 11,83% 14,12% Ijmond PVV, LPF Hard Soft - 18,07% 6,30% 6,46% 16,04% 10,35% 12,81% Against 61,62% 64,71% 2,68% 6,18% 5,98% 6,26% 16,04% 10,35% 15,14% 1,91% 19,20% 7,23% 19,32% 12,56% 15,01% 17,34% Alkmaar PVV, LPF Hard Soft - 15,13% 5,10% 5,80% 12,84% 9,75% 10,35% Against 60,11% 62,17% 2,70% 6,07% 5,85% 5,56% 12,84% 9,75% 12,43% 1,98% 16,52% 6,01% 18,50% 11,85% 14,26% 16,97%
Oost-Groningen PVV, LPF Hard Soft - 15,67% 4,28% 4,31% 1796% 11,06% 18,82% Against 76,08% 70,40% 4,58% 5,72% 6,26% 4,15% 17,96% 11,06% 20,58% 5,39% 19,40% 7,29% 22,26% 19,97% 21,78% 30,80%
COROP region Mean import shock Max import shock Min import shock Mean PVV/LPF Mean hard skeptic Mean soft skeptic Noord-Limburg .9443 1.9143 .2626 .1431 .1147 .1441 Zuid-Limburg 1.2536 2.47339 .3856 .1454 .1411 .1488 Midden-Limburg 2.6875 5.65051 .8179 .1455 .1301 .1379 Flevoland .4681 .97678 .1537 .0909 .0807 .2317 Zuidoost-Noord-Brabant 1.5780 3.27945 .6063 .0993 .0920 .1396 Noordoost-Noord-Brabant .5082 .9694 .1691 .0950 .1018 .1566 Middennoord-Brabant .7163 1.3469 .2642 .0946 .0880 .1379 Westnoord-Brabant 1.3273 2.6293 .4280 .1293 .1149 .1417 Overig Zeeland 1.3562 2.82058 .4671 .0844 .0757 .2584 Zeeuwsch-Vlaanderen .7968 1.6702 .03854 .1157 .0981 .1644 Zuidoost-Zuid-Holland 1.8985 4.16033 .6063 .0909 .0747 .2696 Groot-Rijnmond .7167 1.4649 .2396 .1248 .0981 .2132 Oost-Zuid-Holland .2455 .4561 .05305 .0950 .0774 .1878 Delft en Westland .3707 .6775 .1317 .0938 .0875 .1203 Agglomeratie 'S-Gravenhage .2557 .5465 .0852 .1107 .0912 .1304 Agglomeratie Leiden en Bollestreek .7807 1.7058 .2567 .0906 .0765 .1344 Het Gooi en Vechtstreek .6121 .9873 .2258 .0766 .0669 .1167 Groot-Amsterdam .7898 1.7937 .2491 .1030 .0874 .1223 Zaanstreek .4012 .7488 .1013 .1007 .0959 .1529 Agglomeratie Haarlem .2778 .5149 .06031 .0830 .0703 .1102 Ijmond .4249 1.3495 -.53761 .1000 .0894 .1322 Alkmaar .3741 .7084 .1361 .0842 .0788 .1229 Kop van
Noord-Friesland .7634 1.7232 .2451 .0682 .0670 .1473 Overig-Groningen .5566 1.1527 .1831 .0633 .0724 .1902 Delfzijl e.o. 1.426 3.03197 .00562 .0789 .1290 .1850
Oost-Groningen .6891 1.4199 .1878 .1030 .1004 .1812
Table 8: Mean import shock, PVV/LPF, hard skeptic parties and soft skeptic parties in the period 1995-2017 by COROP region
Year Mean import shock Mean voting against
2005 1.7876 0.6200
2016 -.5535 0.6251
Table 9: Mean import shock and mean voting behavior for referendum 2005 and 2016
COROP region Mean import shock Mean voting against Noord-Limburg 0.6093 609.4907 Zuid-Limburg 0.6591 823.5567 Midden-Limburg 0.5911 1733.458 Flevoland 0.6912 307.9471 Zuidoost-Noord-Brabant 0.5906 998.5404 Noordoost-Noord-Brabant 0.5920 345.1169 Middennoord-Brabant 0.6219 558.4564 Westnoord-Brabant 0.6498 945.9001 Overig Zeeland 0.6668 980.7629 Zeeuwsch-Vlaanderen 0.6658 814.1552 Zuidoost-Zuid-Holland 0.6927 1286.314 Groot-Rijnmond 0.7008 492.1047 Oost-Zuid-Holland 0.6224 219.2415 Delft en Westland 0.5738 237.7239 Agglomeratie 'S-Gravenhage 0.5897 173.9533 Agglomeratie Leiden en Bollestreek 0.5792 514.7906 Het Gooi en Vechtstreek 0.5607 568.6949 Groot-Amsterdam 0.6222 511.8195
Zaanstreek 0.6749 346.6278
Agglomeratie Haarlem 0.5471 269.9210
Ijmond 0.6317 932.0930
Alkmaar 0.6114 285.1712
Kop van Noord-Holland 0.6412 405.3498
Zuidwest-Drenthe 0.6143 1529.757 Zuidoost-Drenthe 0.6548 601.4984 Noord-Drenthe 0.5733 206.9735 Zuidoost-Friesland 0.6224 762.5785 Zuidwest-Friesland 0.5957 895.3409 Noord-Friesland 0.5991 528.2042 Overig-Groningen 0.5924 397.4874 Delfzijl e.o. 0.6573 1371.966 Oost-Groningen 0.7324 473.8094
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