Tag: China
Russia’s Car Fleet Dynamics – and Why They Matter
Russia’s car imports have evolved dramatically since its full-scale invasion of Ukraine in February 2022. The invasion and subsequent sanctions have led to a shift away from mainly Western car imports to domestically produced cars, and especially Chinese cars, both entailing quality concerns. Despite state sponsored loans reliefs, the heightened inflation pressures in Russia and increased financial burden on households is catching up to the car market – in the first quarter of 2025, the sales of new cars decreased by 25 percent compared to 2024. This policy brief uses the developments in the Russian primary car market as a lens to examine the spending power of Russian households and highlight the limitations of state interventions under sanctions and inflationary pressure.
From Western Dominance to Domestic Car Sales
Prior to February 2022, imports of American, European, South Korean and Japanese (hereafter called western) cars stood for about 60 percent of all new car sales in Russia. Domestic production took up most of the remaining 40 percent market share (SITE, 2024). In 2023, the number of western car sales was almost zero as most of these automotive firms exited the Russian market following the country’s war on Ukraine. Collaborations between European and Russian automotive companies, such as between Renault and Autovaz, as well as production of western cars in Russia, were also largely abolished. The mass exodus severely impacted the production levels in the Russian automotive industry; in 2021 around 1 350 000 cars were produced in Russia, dropping to around 450 000 in 2022, and increasing to only about 750 000 cars in 2024. However, the sales of new Russian cars fell in the immediate months following the invasion and subsequent sanctions but managed to bounce back to initial levels in 2023 (Figure 1).
Figure 1. New car sales in Russia
Source: Association of European Businesses. Note: Detailed data for 2024 and 2025 is unavailable.
The Chinese Import Surge
While the sale of Russian cars rebounded following the invasion, the key market player post-2022 is China. As illustrated in Figure 1, in 2023, the sales of newly produced Chinese cars in Russia were eight times the 2020 figures.
Although the imports of Chinese cars made up for a large part of the massive withdrawals of western cars post-invasion, new issues have arisen. Chinese cars are considered unfit for Russian weather conditions, and spare parts are also considered to be of low quality. Additionally, Chinese cars are reported to survive shorter total mileages (about half, compared to many western brands), and to have poor electronic and ergonomic systems. Still, prices for a Chinese car are generally higher than for a Russian car, mostly due to taxes and import tariffs. To dampen the recent Chinese expansion on the car market (in 2025 accounting for 63 percent of the market), Russia in March 2025, hiked the import tax on Chinese cars from nearly $6000 to $7500. Furthermore, the price of Chinese cars is expected to increase in 2025, following a depreciation of the ruble against the yuan.
High Prices, Large Loans
Not only Chinese cars have met criticism when it comes to quality and price. In summer 2022, Autovaz declared that the 22 model of the classic Lada Granta would be void of air bags, an ABS braking system and a brake assist system, due to a scarcity of imported components. A subset of the model has since been equipped with a driver-seat air bag. Despite such major shortcomings, prices for new Russian-made cars have increased by 67 percent since the onset of the war. These price increases are mirrored on the secondary market where the price for a used foreign car have increased by 60 percent since 2022.
Another feature of the Russia automotive market concerns the large increase in automobile loans granted to businesses and entrepreneurs over the last four years (Figure 2).
Figure 2. Volume of companies’ automobile loans
Source: Rosstat.
While the near doubling in the loan value for companies’ car loans seems large, its growth is small compared to that for individuals. Since the onset of the war, the volume of private car loans has grown more than fivefold. This increase is arguably spurred by the preferential loans scheme for the purchase of new cars, introduced mid-July 2022 and granted to Russians with at least one child under 18, new car owners, people employed within health and education, military personnel and their close relatives, and disabled people. The so-called loan (projected to be in place up until 2027) applies to car purchases in Russia of a maximum 2 million ruble and discounts the price by 20 percent (25 percent for cars sold in the Far East Region). Under this scheme, car loans constituted almost 6 percent of all consumer loans in mid-2024, a sixfold increase in just a year (see Figure 3). This trend has not waned off since 2024. In December 2023, 70 percent of all cars bought in Russia were financed by borrowed funds. The size of an average car loan also grew substantially, around 20 percent, between 2022 and 2023. At the same time, the share of risky borrowers increased. In October 2024, 60 percent of the borrowers had a Debt Service-To-Income (DSTI) Ratio of over 50 percent, indicating that a large segment of car buyers will potentially be unable to repay the debt (CBR, 2024).
Figure 3. Private Automobile Loans
Source: CBR (2024). Note: Figure based on approximation from CBR figure.
Household Strains and Financial Risks
Over the last five years gasoline prices have gone up by about 17 percent (standard petrol), alongside substantial price increases for nearly all major consumption goods in Russia – driven by the rampant inflation. In fact, the price of the Russian consumer basket nearly doubled between February 2022 and August 2024. Progressive income taxes have been introduced for about 3.2 percent of the working population – increasing taxation from 13 percent up to 22 percent. Furthermore, in July 2024, the subsidized mortgages for newly built apartments were scrapped such that all buyers now face a 16-20 percent rate (SITE, 2025). While real wages did increase by 8 to 9 percent in 2023 and 2024, real pensions did not. Furthermore, reported inflation figures are likely severely understated, with actual inflation being around 20, rather than the reported 9.5 percent. If so, the actual real wage growth would be about 0 percent (SITE, 2025).
This undermines the spending power of Russian households, which is now being reflected on the primary car market. There has been a sharp drop in car sales – 25 percent in the first quarter in 2025, and car prices are also on the decline. This, combined with the growing reliance on credit, signals that many consumers are no longer able to make large purchases despite the state driven support scheme – pointing to major affordability issues. Given that the preferential loans scheme will be in place only up until 2027 and that Chinese cars will likely become more expensive, demand may dwindle even further in the years to come. In such situation, the government could be forced to expand their preferential scheme to artificially keep up demand levels, taking on greater financial risks and associated costs. They may also increasingly close off the inflow of Chinese cars, which leave consumers with no options outside of domestically produced cars.
The falling demand for cars may also be considered an indicator of household’s beliefs about the economic conditions to come. That is, the demand for cars could be a signal of consumers understanding that the economy is, or will shortly be in a recession (Attanasio, Larkin, Ravn and Padula, 2022). While the Russian war time economy is not currently displaying recession signs, its persistent issues with rampant inflation, rapidly growing household mortgages and changes in the credit to GDP ratio signals its financial stability is at risk. As discussed in the report “Financing the Russian War Economy”, these are key indicators correlated with banking crises (SITE, 2025). If declining demand for cars is a sign of consumers perceiving the economy as increasingly fragile, this perception could amplify existing vulnerabilities.
Conclusion
The automotive sector offers comparatively timely data, making it a useful window for assessing the financial situation of Russian households. In the current automotive landscape in Russia, buying a new car is becoming increasingly expensive. This has forced not only private buyers but also businesses to increasingly take up loans to cover the payment of a new car – often despite reduced quality and limited choice. The demand for new cars is partly driven by state intervention, particularly the preferential loan scheme. This not only places a growing financial burden on the state but also carries rising risks of borrowers defaulting. At the same time, the current trends in the sector illustrate the growing limitations of both import substitution and state-backed credit schemes as tools for maintaining consumer demand. The recent drop in new car sales, despite state support, may reflect a growing reluctance among households to make large purchases, exposing how Russian households’ purchasing power are eroding in the Russian wartime economy. Importantly, this drop may point not only to affordability issues but also to a broader perception that the financial system is increasingly unstable.
Overall, the dynamics in the automotive sector suggest that the Russian economy is not doing as well as officially claimed, adding support for the effectiveness of sanctions and company withdrawals from the Russian market.
References
- Attanasio, O., Larkin, K., Ravn, M. O., & Padula, M. (2022). “(S)Cars and the Great Recession”. Econometrica, 90(5), 2319–2356.
- The Central Bank of Russia (CBR). (2024). “Financial Stability Review No. 2. Q2-Q3, 2024”.
- Stockholm Institute of Transition Economics (SITE). (2024). “The Russian Economy in the Fog of War”.
- Stockholm Institute of Transition Economics (SITE). (2025). “Financing the Russian War Economy”.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Democratic Backsliding and Electoral Autocracies: Research Shared at the 2023 FROMDEE Conference
On October 13th, 2023, the Stockholm Institute of Transition Economics (SITE) and the Forum for Research on Media and Democracy in Eastern Europe (FROMDEE) hosted an academic conference on “Democratic Backsliding and Electoral Autocracies”. This brief provides a short summary of the keynote lecture and research presentations featured at the conference.
The most recent report by the V-Dem Institute concludes that “72 percent of the world’s population […] live in autocracies by 2022” and “the level of democracy enjoyed by the average global citizen in 2022 is down to 1986 levels” (V-Dem Institute, 2023). In Europe, these declines have manifested in the previous Polish government undermining judicial independence, in tightened political repression in Belarus, and most prominently in Putin’s invasion of Ukraine. But the rise of electoral autocracies and democratic backsliding are not confined to Europe – their strategies of propaganda, corruption, electoral manipulation, as well as attacks on judicial and media independence are a global phenomenon. The October 13th FROMDEE Conference gathered researchers from economics, law and political science to bring insight into why and where reversals are taking place, and what measures are needed to reverse the negative trend. This policy brief provides an overview of the research shared at the conference.
Populism and Autocracy – the Case of Russia
In the keynote lecture, Arturas Rozenas (New York University) focused on the roots of populism, challenging the common view of illiberal democracies as a mix between democracies and dictatorships. Rather, dictatorships evolve into populist dictatorships that then take one of two paths: either the path to democracy, or the path towards electoral autocracy, illiberal democracy, or totalitarianism. In this framework, populist dictatorships have historically made use of populist elements we recognize from modern times, i.e., democratic-seeming institutions misused for the ruler’s purposes.
In a populist dictatorship, Rozenas continued, there is a monopoly of power. Institutions such as elections and parliamentary representation, serve not to allocate power but to legitimise it. The transition from passive to active dictatorships coincided with a move away from the common notion of a king or similar leader deriving rightful power from God to rule the masses, to a reality built on the idea that the ruler’s legitimacy stems from the masses. This historic transformation should however not be interpreted as a transition to democracy. In fact, Rozenas showed that for most of recent history, the majority of elections and expansions of suffrage took place in dictatorships rather than in democracies. These seemingly populist institutions serve not only to legitimise governments, but also to coopt the population in a public display of the ruler’s strength. Rozenas argued, that in an active populist dictatorship, the ruler creates a setting which suppresses dissent and expectations of dissent, through institutionalised expressions of support (in the form of political participation, elections, large rallies etc.).
Turning to the Russian setting, the first thing to notice is the deep tradition of autocracy – from tsarism to Stalinism. In Russia, the words “society” and “the people” briefly blossomed during past revolutions or uprisings but have largely been absent in the Russian language and are once again on the decline under the rule of Putin. Further, the Russian population has time and again been exploited by its rulers during succession crises for displays of power and dominance. Examples of this are the mandatory elections held under Stalin two weeks after the invasion of the Baltic States in 1939 and more recently under Putin in the occupied territories of Luhansk and Donetsk in Ukraine in 2021. Such populist autocratic strategies are nothing new in Russia, concluded Rozenas – rather they derive from the internal logic of dictatorship that has played out throughout Russian history.
Continuing the notion of the “absent” Russian society, Olha Zadorozhna (Kozminski University) began her presentation by explaining that protests are infrequent in Russia and have surprisingly few attendees given the country’s large population. While there were mass protests in the run-up to the collapse of communism in the 1980’s and protests took place against corruption in 2017-2018, and in relation to the arrest of Alexey Navalny in 2021, protests in Russia are typically not motivated by an overarching ideology or broader political questions. Rallies in favor of authoritarianism and ethno-nationalism are a more common occurrence. Moreover, there are few indications that the invasion of Ukraine, sanctions and subsequent economic downturn have negatively affected the Russian population’s support for the regime. Still, literature has shown that war-related deaths can mobilize opposition against war participation (e.g., the U.S. participation in the Vietnam War). Considering this, Zadorozhna evaluates whether the deaths of Russian soldiers provoke a reaction among the Russian population. By combining social media data on fallen soldiers with protest activity for the first four months of the Russian invasion in 2022, the study find that casualties lead to an increase in protest activity, indicating that deaths can in fact mobilize public opposition in Russia.
Other populist strategies to ensure support for Putin in Russia relate to political participation and the judiciary. Nicholas James (University of Oxford) analysed electoral rule changes in the Russian Duma – from mixed member majoritarianism to proportional representation (PR) – by measuring their effect on floor participation. Applying a difference-in-differences framework, James found that deputies experiencing a change from PR included less words in their speeches following the switch (about 15-20 percent of an average speech). This effect should be understood in the political context of the ruling party’s (United Russia) increased influence during this time period (2010s). In fact, James concluded, the results point in the direction of the regime tampering with the Duma in an impromptu and reactionary manner with the overall goal of obtaining closer control and the appearance of support for the regime.
Yulia Khalikova’s (University of Hamburg) presentation gave further insight into how ostensibly democratic institutions can be exploited to make an authoritarian regime appear legitimate. In her work, Khalikova considers judicial references to international law that may be employed strategically, without necessarily adhering to the spirit or content of the law. Looking specifically at international law citations in 601 judgements made in the Russian Constitutional Court (RCC) between 2000 and 2021, Khalikova find evidence that the RCC has increasingly cited international courts when making judgements on topics related to politics and physical rights, indicating that state policy influences citation patterns. The change in citation patterns also points to the RCC currently using international law to support the regime and uphold its legitimacy, meaning that international law – adopted with the ambition of enhancing democratic values and ensuring human rights – is misused for undemocratic and repressive purposes.
Censorship and Propaganda
Information control is an important feature of autocratic regimes. Philine Widmer (ETH Zurich) considers the Chinese setting – where the regime controls the amount of foreign information available on the internet via a countrywide firewall. Research has shown that autocracies make use of censorship strategies to control their citizens, but these are associated with high reputational costs and can be overcome by tech-savvy citizens. Using a machine learning algorithm, Widmer first predicts a newspaper article’s alignment with the Chinese regime before comparing the placement of more/less aligned articles on news websites. Her results show that front-page news stories in Chinese newspapers are more aligned with the regime’s stance than other content. Front-page placement in turn matters for information uptake. Widmer ended the presentation by comparing the additional cost of finding less aligned articles to the technological costs required to access outside media (e.g. VPNs). For an autocracy to achieve its information control objectives, independent news may just need to be relatively harder to access. It does not need to make it impossible to access for all citizens.
Censorship is typically accompanied by, and complementary with, propaganda. Restricting other narratives allows autocratic regimes to spread their own. While propaganda is a common feature within autocracies, Jaakko Meriläinen’s (Stockholm School of Economics) presentation evaluated the effect of autocratic propaganda in a democratic setting.
Meriläinen’s study focuses on a rogue experiment in which some Finnish children in the 1970’s were taught history and social sciences using material from the Soviet Union – material which was in essence Soviet propaganda. By exploiting geographical and cohort variation, Meriläinen use a difference-in-differences approach to compare the 213 exposed children to children taught the regular Finnish curriculum. The long-term outcomes show that exposed children had lower incomes in adulthood, worked fewer months per year and were engaged in more left-leaning and publicly beneficial occupations (such as, nurses and firefighters).
Information and Accountability
The use of technological innovations to access otherwise restricted information was central to Arieda Muço’s (Central European University) presentation. She studies the spread of the Xerox photocopying machine in communist Hungary in the 1980’s – a setting characterised by limited freedom of speech and restrictions on the media. She reported that areas with early placement of Xerox machines are found to exhibit higher shares of pro-democratic voting. Muço ascribes these outcomes to the fact that the machines allowed for the spread of information and eased coordination of the opposition, suggesting that new technologies and information can act as key facilitators in the fall of autocratic regimes.
Providing citizens with information was also a key feature in Enrique Seira Bejarano’s (Michigan State University) presentation. He began by discussing two potentially related trends: in Latin America recent years have seen (i) increased levels of corruption and (ii) increased dissatisfaction with democracy among citizens. The number of corruption-related news articles have increased threefold in Spanish and doubled in English and the share of people perceiving corruption to be the greatest challenge to their country has doubled in the last decade. The study uses two empirical strategies to identify the effect of corruption on democratic values. Firstly, Seira Bejarano described an observational study, in which data on major corruption scandals were combined with Latinobarometer data on support for democracy. The authors find that corruption scandals increase corruption perceptions while decreasing stated support for democracy. Secondly, Seira Bejarano reported the results of a randomized controlled trial in which some respondents were shown videos of a politician accepting bribes. This had a negative effect on preferences for democracy and on trust more broadly. Both studies show that revelations of corruptions decrease the support for democracy, suggesting a potential tradeoff between the public’s belief in democratic institutions and increased transparency which is important for accountability but can also expose corruption.
Right-wing Populism
Yet another threat to democracy is the rise of right-wing populism – currently a reality in many well-established democracies across Europe. In Germany, the far-right party Alternative für Deutschland (AfD) enjoys around 21 percent of voters’ support according to recent polls. To understand their rise in popularity, Navid Sabet (Goethe University Frankfurt) builds on previous literature on cultural conflict as a driver for right-wing party support. The paper he presented examines the role of violent conflict in the form of terrorist acts. It evaluates whether acts of terror can alter the political landscape and shift support to the far-right. To avoid selection problems, the authors compare successful terror attacks to attacks that failed. Sabet reported that successful small-scale attacks (predominantly targeting migrants) increase AfD’s vote share by about 6 percentage points in state elections (in the time period 2013-2021). The acts of terror were found to increase voter turnout, by mobilizing otherwise idle voters, but also by gaining votes at the cost of other parties. Exploring the mechanisms behind these results, the authors study the language used by political parties and the way successful attacks were covered in the media. Relative to coverage of unsuccessful attacks, media coverage used a more negative tone, more words related to Islam and terror and fewer words related to right-wing populism. This suggests that media plays an important role in shaping the public’s response to acts of terror and that far right parties are able to exploit this dynamic.
Concluding Remarks
The 2023 FROMDEE Conference brought together academics from different fields to shed light on some of the main challenges to democracy today. In part, the research presented supported the prevailing narrative that democracies are backsliding in many parts of the world. However, by analysing how autocracies and populist leaders operate, the presenters also highlighted the vulnerability of dictatorships.
Arturas Rozenas cited the example of a rally in Bucharest in 1989, which was organised to display support for Ceauşescu’s regime and descended into an anti-government protest. Dictatorships can benefit by coopting the populist elements of democracy but, in doing so, they risk creating a vehicle for genuine democratic expression.
The audience learned about autocracies’ efforts to control the flow of information but also about citizens’ ability to circumvent restrictions whether in 1980s Hungary or present-day China. Several presentations focused on the extent of autocratic control in Russia but even in this setting, the death of soldiers in Ukraine motivates citizens to participate in protests.
Recent trends suggest that democratic institutions should not be taken for granted in any country. Societies can become more resilient to the threat of democratic backsliding, in part by better understanding how both democracies and autocracies operate and what makes them vulnerable. Researchers around the world are using innovative methods to expand our knowledge in this area, as reflected in the presentations at the 2023 FROMDEE Conference.
References
- V-Dem Institute. (2023). Defiance in the Face of Autocratization. Democracy Report 2023. University of Gothenburg. Varieties of Democracy Institute (V-Dem Institute). https://www.v-dem.net/publications/democracy-reports/
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Trade Induced Technological Change: Did Chinese Competition Increase Innovation in Europe?
The last 30 years has witnessed a shift of the world’s manufacturing core from Europe and North America to China. A key question is what impact this has had on manufacturing workers in other developed economies, and also on innovation, patenting, IT adoption, and productivity growth. While a rigorous data analysis on these variables for developing economies, particularly in Eastern Europe, is not yet available, this brief examines the impact of the rise of China on innovation in Western Europe, and also reviews the evidence on the impact of the rise of China generally. Recent research by Bloom, Draca, and Van Reenen (2016) found that Chinese competition induced a rise in patenting, IT adoption, and TFP by 30% of the total increase in Europe in the early 2000s. Yet, we find numerous problems with the Bloom et al. analysis, and, overall, we do not find convincing evidence that Chinese competition increased innovation in Europe.
Few events have inspired the ire of economists as much as Brexit and the rise of Donald Trump, two events seen as related as both were a seeming reaction to both globalization and slowing economic growth, particularly as some (such as Trump himself) saw the former as a key cause of the latter. Both Brexit and the trade war spawned by Trump do seem to have had negative economic effects – US equities have suffered every time the trade war has escalated, while anecdotal reports and more sophisticated economic analyses seem to suggest that Brexit has cost the UK jobs.
And yet, there is a need for policy makers and economists to hold two ideas in our heads simultaneously: Trump’s trade war and Brexit may be policy disasters, and yet globalization can create both winners and losers, even if it is clear that, generally speaking, the overall gains are likely positive and large. This is likely also true of the rise of China – one of the most dramatic events in international economics in the past 50 years. Figure 1 shows the increase in trade with China from the early 1980s to 2017, a period in which US imports from China grew from 7 to 476 billion dollars.
Figure 1. Chinese Imports (in logs, deflated)
Source: World Bank WITS
The academic literature tends to show that this impact, the rise of China, may have cost the US as much as 2.2 million jobs directly (Autor et al.), and as much as 3 million jobs once all input-output and local labor market effects are included. While approximate, these numbers are large enough for the China shock to have played a role in the initial onset of “secular stagnation” – the growth slowdown which began around 2000 for many advanced nations, including the US and Europe. In addition, Autor et al. (forthcoming) found that Chinese competition also resulted in a decline in patent growth. In the European context, however, other authors have found that although China did do some damage to certain sectors, overall, it does not appear to have been quite as damaging, particularly in Germany, which also benefitted from exporting increased machine tools to the Chinese manufacturing sector. And, in a seminal paper, Bloom, Draca, and Van Reenen (2016) find that Chinese competition actually led to an increase in patents, IT adoption, and productivity in Europe from 1996 to 2005, along accounting for nearly 30% of the increase. This is important, as it implies that without the rise of competition with China, the slowdown in European growth would have been even more pronounced than it was. It also implies that, far from being a source of stagnation, Chinese competition has been a source of strength. It also makes it more likely that the slowdown in growth since 2000 was caused by supply-side factors, such as new inventions becoming more difficult over time, as is perhaps the leading explanation among economists, notably Northwestern University business professor, Robert Gordon (2017), and also supported by others (see this VoxEU Ebook featuring a “who’s who?” among economists). It would also be evidence that contradicts the “Bernanke Hypothesis” that the former US Fed Chair first laid out in a 2005 speech at Jackson Hole, in which he suggested that international factors – particularly the savings glut and US trade deficit – were behind falling interest rates in the US. Since then, Ben Bernanke has followed up with a series of blog posts suggesting that these international factors were the cause of the initial onset of secular stagnation.
Figure 2. European Growth Relative to Trend
Source: World Bank WDI
In this brief, I present new research in which my coauthor and I test the robustness of the research finding that China had a positive impact on innovation in Europe (Campbell and Mau, 2019). We find that these findings are very sensitive to controls for time trends and other slight changes in specification. We also find that the number of patents matched to firms in the sample shrinks over the sample period (from 1996 to 2005). Overall, we conclude that, unfortunately, it is unlikely that the rise led to a significant increase in innovation in Europe, although more research is needed. Our research also sheds light on the so-called “replication crisis” currently gripping the social sciences, as researchers begin to realize that many published findings are not robust.
Trade-Induced Technical Change?
Bloom, Draca, and Van Reenen (2016) – hereafter BDV – tried to isolate the impact of the rise of China on Europe using several methods, using firm-level data for Europe. They placed each firm in a 4-digit sector, where they measured imports from China over time. First, they just looked at changes in patents, IT, and total factor productivity (TFP) at the firm level for sectors in which Chinese imports increased a lot vs. other sectors. But, because economists are always weary of the difficulty of isolating a causal relationship from non-experimental data, the authors, worrying that the sectors which saw increases in Chinese imports might differ systematically from the others, the authors also used what is called an instrumental variable. That is, they used the fact that when China joined the WTO in 2001, they also negotiated a reduction in textile quotas. Thus, BDV reason that textile sectors which had tightly binding quotas prior to removal were likely to have had fast growth in Chinese imports after China’s accession to the WTO. Thus, they end up comparing textile sectors in which the quotas were binding to sectors in which they were not binding. We went back and compared the evolution of patents in these same groups (sectors with binding textile quotas vs. not binding) below in Figure 3.
Figure 3. Patent Growth in China-Competing Sectors (Quota Group) vs. Other Sectors
Notes: The vertical red lines are dates when textile quotas were removed. The blue line shows the evolution of patents in the sectors without binding quotas (non-competing sectors), and the red line is the evolution of patents in the China-competing sectors. The dotted lines are 2 standard deviation error bounds.
What is immediately obvious in Figure 3 is that patents are declining rapidly over the whole period in both groups. The overall level of patents was falling in both groups for the full period. There is a 95.8% decline in patenting for the China-competing group, vs. a 96.2% decline for firms in the non-competing (“No quota”) group. By 2005, average patents per firm are close to zero in both groups (.04 in the China-competing sectors vs. .11 in the others). However, in the “No quota” group, the initial level of patents – close to three per firm per year – was much larger than in the quota group. Since patents are falling rapidly in both groups but bounded by zero, the level of the fall in patents in the non-quota group is larger, but one can easily see that much of this decline happens before quotas are removed. If we control for simple time trends, the effect goes away. Also, given the tendency of patents to decline, we can also remove the correlation between Chinese competition and patent growth in some specifications by simply controlling for the lagged level of patents. The overall declining share of patents in the BDV data also raises questions about data selection issues, as patents granted in the BDV data in the later years were a smaller share of the total patents actually granted in reality.
BDV also look at the impact of the rise of China on IT adoption. However, here they proxied IT adoption by computers per worker, but they did not collect enough data to control for pre-trends properly in the data, so we cannot be sure whether this correlation is causal or not. (For what it is worth, on the data we do have, from 2000 to 2007, including trends in the data renders the apparent correlation between Chinese import growth and computers-per-worker insignificant.)
Lastly, BDV look at the impact of the rise of China on TFP growth. Here, unlike before, we find that their measure is robust across various estimation methodologies. However, when we look at changes in a commonly used alternative measure of productivity, value-added per worker, instead of TFP (as TFP needs to be calculated using strong assumptions about the functional form of technology), we find no impact (see Figure 4 below).
Figure 4. Value-Added per worker Growth: China-competing sectors vs. others
Figure 4 above compares the evolution of value-added per worker in the most China-competing sectors vs. the others. Trends look similar for firms in either group of sectors (China-competing or otherwise), and we do not find a correlation. We also do not find that Chinese competition led to an increase in profits, nor an increase in sales per worker (in fact, we found a significant decrease in most specifications).
Conclusion
All in all, we find that the BDV findings suggesting that the rise of China had a large impact on innovation in Europe is not robust. However, in most specifications, we also don’t find a negative impact as did Autor et al. (forthcoming) for the US. This might have to do with data quality, although it does seem to be closer to other work, such as Dauth et al. (2014), which suggests that the rise of China had a smaller impact in Germany than in the US.
We also felt it was a bit alarming that a simple plot of the trends in patents for China-competing and not-competing sectors was enough to seriously question the conclusions of BDV, as their paper was published in the Review of Economic Studies, a top 5 journal in academic economics. If influential articles published in the most fancy journals can exhibit such mistakes, this underscores the extent which the profession of economics may suffer from many published “false-positive” results. The reasons why this could be the case are obvious: researchers are under pressure to find significant results, as top journals don’t often publish null results, and replication is exceedingly rare in a field in which one needs to make friends to publish. However, there are signs that replication is becoming more mainstream, and as it does, we can certainly hope that voters around the world will turn back to science.
References
- Autor, D., D. Dorn, G. H. Hanson, G. Pisano, and P. Shu. Forthcoming. Foreign Competition and Domestic Innovation: Evidence from US Patents. Forthcoming: AEJ:Insights.
- Bloom, N., M. Draca, and J. Van Reenen. 2016. “Trade Induced Technical Change? The Impact of Chinese Imports on Innovation, IT and Productivity.” The Review of Economic Studies 83 (1): 87–117.
- Campbell, Douglas and Mau, Karsten. 2019.. Trade Induced Technological Change: Did Chinese Competition Increase Innovation in Europe?”, mimeo
- Dauth, W., S. Findeisen, and J. Suedekum. 2014. “The Rise of the East and the Far East: German Labor Markets and Trade Integration.” Journal of the European Economic Association 12 (6): 1643–1675.
- Gordon, R.J., 2017. The rise and fall of American growth: The US standard of living since the civil war (Vol. 70). Princeton University Press.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
US-China Trade War of 2018 and Its Consequences
The trade war between the United States and China has become one of the main events in the global economy this year. What could be its consequences for the US and China, and how might it affect other countries – for example, Russia?
Chronology of the trade war
Donald Trump started the war, raising import tariffs on solar panels in January 2018, of which the main supplier is China. In response, on April 2nd, China raised import duties on 128 commodities originating from the United States. On July 6th, the US increased tariffs on Chinese goods by 25 pp., imports worth $34 billion. China responded symmetrically. In August, the United States increased the tariffs on another $16 billion of imported goods from China, to which a symmetrical response again followed. In September, the United States again applied higher tariffs for $200 billion of Chinese exports, and China for $60 billion of US exports. At each stage of the conflict escalation, China appealed to the WTO with complaints about the actions of the United States, pointing to the inconsistency of their actions with the obligations and principles of the WTO. There were several meetings of official representatives from the United States and China – without any significant results.
What are the main reasons for this unprecedented escalation?
Imbalance and intellectual property
The economies of the US and China today are by far the largest in the world, and the trade turnover between the two countries is one of the most important. A remarkable feature of these trade flows over last decades is their imbalance. In 2017, the United States imported $526 billion worth of goods from China, while China’s imports from the United States amounted to $154 billion. Part of this imbalance is offset by trade in services, but it is not enough to even it out: in the same the year the United States delivered $57 billion worth of services to China while importing services of $17 billion from China.
Experts have different views on this imbalance. On the one hand, there is a perception that it is a source of world economy vulnerability, a source of potential crisis. Therefore, it is necessary to reduce the trade deficit. Another point of view is that this imbalance merely reflects the fact that the US economy and its assets are very attractive to investors from all over the world, including Chinese – and that, in turn, requires that the surplus of capital flows biased to US side, was compensated by the corresponding deficit of trade in goods and services. One such investor is the Chinese state itself, which for many years has been pursuing a policy of exchange rate undervaluation in order to promote foreign trade. It led to an enormous accumulation of foreign exchange reserves and as of January 2018, China held $1.17 trillion of US bonds and was the largest creditor of US government.
US President Donald Trump referred to this trade imbalance as one of the reasons for the outbreak of this trade war against China. Trump aims at reducing the deficit by $100 billion from the current $375 billion. The unilateral increase in import tariffs applied to Chinese goods was the first action of the US administration in this direction.
The second, no less important, formal reason for the trade war is the inadequate protection of intellectual property rights in China. China’s production of counterfeit products, the lack of adequate practices and laws to protect foreign technologies from illegal dissemination in the country, is not news to anyone. And although the almost two decades since China’s WTO accession have meant a largely modernized legal framework in this regard, a number of important provisions are still inconsistent with international practices, and the implementation of existing intellectual property rights leaves much to be desired. Established in 2012, The Commission on the Theft of American Intellectual Property identifies China as the most malicious violator of US rights. The exact damage is not known, but the commission assessment of the losses to the American economy due to the forced transfer of technology to Chinese partners – which is an unspoken condition of foreign manufacturers access to the Chinese market – industrial espionage, contradictions in legislation, requirements for the storage of sensitive data in China are in the range from $225 to $600 billion per year (Office of US Trade Representative, 2018).
While both the trade deficit and the intellectual property rights issue were recognized for many years, it was in 2018 that Trump started acting on them. Therefore, in order to discuss the potential impact of the conflict between the world’s largest economies on themselves and other economies, such as Russia, it is important to understand what drives the actions undertaken by Trump’s administration.
Populism
Trump won the elections in 2016 with a minimum margin against the Democratic rival. To provide support for his decisions and to increase the chances of being reelected for the next term in 2020, it is crucial to maximize the pool of his supporters. Trade policy measures aimed at import substitution are very effective populist policies in any country. One of the first steps made by the US toward trade war was the increase in import tariffs on steel and aluminum – for all countries. Metallurgy and coal industries are among the most organized and strong lobbyists in any country. The European Union as an economic organization started with the European Coal and Steel Association. By aligning interests with these sectors much can be achieved in relation to trade liberalization, and vice versa – by increasing the level of protectionism, a significant popularity increase can be among voters whose incomes depend on the success of companies in these industries.
Deterrence
China works hard raising the technological level of its economy. In recent years the Chinese government and Communist party launched a number of ambitious programs aimed at achieving a technological breakthrough, lessening the dependence on imported technologies by substituting them with ones produced by domestic innovation centers. These programs specify the priority sectors, in which state subsidies are provided for the acquisition of foreign technologies by Chinese companies and their adaptation. One of the common arguments was that the United States believes that powerful state support for technology sectors in China, along with the existing problems in protecting intellectual property rights, increases the risks and potential losses of American companies.
However, while these concerns seem reasonable at first, they should not be taken at the face value.
China’s ability to push out American companies in the high-tech sector on the world market seems rather limited. So far, China has only succeeded in increasing its share in the middle and low technology segments. Instead, in recent years, China is rapidly increasing its defense spending, which in 2017, for the first time, reached a level of 1 trillion yuan (about $150 billion). China’s defense spending is the second highest in the world after the United States. Moreover, it’s growing very fast. While in 2005 the Chinese nominal defense expenses were only 10% of American expenses, in 2018 they are already around 40%. The dominance of state enterprises in the defense industry in China implies that the real purchasing value of these expenditures is quite comparable. New and existing Chinese industrial policy programs target military and dual-use industries among others. Therefore whilst addressing the intellectual property rights problem in China now, Trump’s administration also aims at preserving US leadership position in the military sector, which finds widespread support in Trump’s main voter groups among Republicans.
Obsolete weapon
Historically, trade wars implied tariff escalations to protect domestic industries from foreign competition. Today, the Trump administration behaves in a similar manner. However, the circumstances now are fundamentally different from those in the first half of 20th century and earlier. Firms not only trade in final goods, but more and more they trade in intermediate products and within firms themselves (Baldwin, 2012). The distribution of the production process to many companies across different countries of the world leads to two important effects, which were not observed in previous trade wars.
First, it is the effect of the escalation of tariff protection in the framework of the value chains. The import tariff is applied to the gross value of the product crossing the customs border. However, the exporting firm’s contribution to the gross value might be quite small. So the effective level of the tariff will be higher than the nominal level of the tariff, known as a so called amplification effect (World Bank, 2017, page 98). It means that the effective growth of the tariff by 25 percentage points in relation to Chinese imports will significantly exceed 25 % and in some cases can even become prohibitive. So, the tariff warfare will result in significantly greater losses for the sectors involved in the value chains, compared to the sectors less exposed to them. It means that foreign investors and multinational companies in China will suffer bigger losses compared to purely domestic Chinese companies. The Peterson Institute for International Economics made an assessment and confirmed these observations (Lovely and Yang, 2018).
Second, China’s participation in international multinational companies most often occurs in the assembly segments, while developed countries’ companies contribute at other stages, such as with innovation, design, financial and consulting services, marketing, and after-sales services. Then, the protectionist measures against goods produced in China by multinational companies will hit an American economy, generating losses in the service segments. A similar episode happened, for example, in 2006, when the European Union introduced anti-dumping duties on imported footwear from China and Vietnam, which in turn lead to a decline in the services sector in Europe – imported footwear contained a significant share of the value added created by European designers and distributors (World Bank, 2017). Obviously, we will observe the same consequences in the United States now, since the role of the American services sector in creating and promoting Chinese goods on the American market is significant and according to World Bank estimates in 2011, the contribution of value added generated by foreign services in China’s gross exports amounted to about 15% (World Bank, 2017).
Thus, not only the economy of China, but also the US economy itself will suffer from the growth of import tariffs in the USA. The USA is not an exception here – the governments of most countries continue to live in the paradigm of trade policy, which suits the structure of the world trade as at the beginning of the 20th century, while trade has gone far ahead and requires much more elaborate effective regulatory tools than tariffs on imported goods.
Consequences for Russia
The consequences of the US trade war with China for the Russian economy depend on what the main goals of the war are. If the motive is primarily electoral – to secure enough support in 2020, one can expect that the protective measures will be short-lived, and the geographical distribution of investment flows will remain almost intact and that China will remain an important location for global value chains transactions. The trade war will in this case lead to some economic slowdown in the short term. The main effects will be related to the redistribution of income within economies, where protected sectors will benefit on the expense of all other sectors. In these circumstances, Russia would suffer direct losses from the growth of tariffs on their exports to US (now it is predominantly steel and aluminum), but for the economy as a whole, the losses will not be significant, especially relative to the losses Russia bears because of sanctions.
However, if the main reason for the trade war has a long-term perspective, the investors will be forced to adjust the geography of their investment plans and China will face a significant outflow of foreign investments, which will significantly affect Chinese – and global – economic growth. In this case, both for Russia and for the whole world, the indirect effect of the US-Chinese trade conflict will be quite noticeable and it will take years to create new trade links and restore world trade and global value chains.
References
- Baldwin, Richard, 2012. “Global supply chains: why they emerged, why they matter, and where they are going”, CTEI Working papers 2012-13, The Graduate Institute, Geneve
- Lovely, Mary E., and Liang Yang, 2018. “Revised Tariffs Against China Hit Chinese Non-Supply Chains Even Harder.” PIIE Policy brief, Peterson Institute
- Office of the US Trade Representative. March 22, 2018. “Executive office of the President findings of the investigation into China’s acts, policies, and practices related to technology transfer, intellectual property, and innovation under section 301 of the trade act of 1974.” https://ustr.gov/sites/default/files/Section%20301%20FINAL.PDF
- World Bank, 2017. “Measuring and analyzing the impact of GVCs on economic development”. World Bank, Washington DC.
Note
A longer version of this brief has been published in Russian by Republic: https://republic.ru/posts/92217
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Leniency, Asymmetric Punishment and Corruption: Evidence from China
Since coming into office two years ago, Chinese President Xi Jinping has carried out a sweeping, highly publicized anticorruption campaign. Skeptics are debating whether the campaign is biased towards Mr. Xi’s rivals, and even possibly related to the current economic slowdown. What is less debated is the next stage of Mr. Xi’s anti-corruption strategy, which is going to alter the legal statutes. Amendment IX, proposed in October 2014, includes heavier penalties, but two important tools in the fight of corruption – one-sided leniency and asymmetric punishment – became more limited and discretional. We argue that studying a 1997 reform and its effects can shed some light onto why the Chinese leadership seems dissatisfied with the current legislation and the likely effects of the proposed changes.
What We Know about Leniency
In our context, leniency can be defined as the concession of reduced sanctions (or full immunity) to wrongdoers that cooperate by self-reporting and providing information against former partners in crime. Formal and informal exchanges of leniency against information and collaboration are normal features of law enforcement in most countries. Policies of this kind have been extensively and quite successfully used to fight the Italian and American mafias, drug dealing and other organized crimes, and have become the main instrument to fight collusion in antitrust since the US reform in 1993 (see Spagnolo, 2008).
For crimes in which multiple offenders cooperate, one-sided leniency conditional on being the first to self-report can be a very powerful tool of law enforcement: by playing the partners in crime against each other, it may elicit information, greatly facilitate prosecution and generate deterrence at a very low cost. A conspicuous scientific literature with theoretical, experimental and empirical contributions shows the great potential of these policies, when properly designed and administered, for deterring collusive crimes (Miller 2009; Spagnolo 2008; Bigoni et al. 2012, 2015). On the other hand, Buccirossi and Spagnolo (2006) show specifically for the case of corruption that, when poorly designed or administered, these same policies may become ineffective or even counterproductive.
Asymmetric Punishment
A related way of using leniency towards one party (to play it against the other) in the fight against corruption has been at the center of a recent intense policy debate after the popular note “Why, for a Class of Bribes, the Act of Giving a Bribe Should Be Treated as Legal”, by Kaushik Basu (2011). Then chief economist of the Indian government and now of the World Bank, Basu advocated asymmetric depenalization of bribe giving, which can be thought of as a form of unconditional, one-sided leniency. More precisely, the note proposed to legalize bribe giving in the form of harassment bribes (also called extortionary, or discharge-of-duty bribes) paid to obtain something one is entitled to, while strengthening sanctions against bribe taking. As with other forms of leniency, the idea is to create a conflict of interests between the partners in crime by increasing the temptation for one party to betray and report the illegal act, leading to a severe punishment of the other.
In the debate sparked by this note many different arguments have been put forward, both against it and in favor of it. Dufwenberg and Spagnolo (2015) discuss formally some of the issues raised by critics of the proposal, while Abbink et al. (2014) provide (mixed) experimental evidence on its effectiveness. Later, a blogpost by a Chinese law scholar, Li (2012), attracted our attention to the case of China, where asymmetric punishment (bribe-giver impunity) has been in place since 1997. She argued, probably reflecting the political debate in the country rather than based on factual evidence, that the system had not been successful. We felt this claim granted a deeper investigation into the details of the Chinese legal reform and the changes it introduced, and of course a careful inspection of the data to back it.
A Study in Red
In a new working paper, Perrotta Berlin and Spagnolo (2015), we set out to understand the evolution of the anti-corruption legislation in China over the last decades, and then to evaluate the effects of the policy changes occurring in 1997. Two new elements were given the strongest legal status in 1997: leniency for wrongdoers that self-reported and cooperated with investigators, and asymmetric punishment (no charge for bribe givers) for bribes paid to obtain something one was entitled to. Concurrently, penalties were decreased, in particular for bribe-takers.
To understand the likely effects of this policy change we would ideally look at correspondent changes in corrupt transactions. Data on the prevalence of bribery, however, are notoriously hard to come by because of the secretive nature of this activity. Instead, we use several data sources which capture on the one hand actual corruption cases tried in courts, and on the other hand surveys of corruption perceptions. In particular, we have collected the number of arrests and public prosecutions on the counts of corruption and bribery from the Procuratorates’ Yearly Reports for each Chinese province since 1986.
It is not straightforward to infer changes in total corruption, which is unobserved, from changes in discovered cases tried in court. The data on prosecutions mix together corruption and anticorruption activities, as they fail to distinguish occurrence of the criminal activity from detection. A policy that deters crimes but at the same time increases the fraction of those that are successfully prosecuted will have an ambiguous effect on the number of prosecutions. We adapt for this purpose the testable predictions developed by Miller (2009): he models the occurrence of criminal activity (cartel formation, in this case) and derives predictions for how changes in the rate of occurrence and the rate of detection affect the time series of detection.
The preliminary evidence we have so far points to a substantial and stable reduction in the number of major corruption cases around the 1997 reform, a result consistent with a positive deterrence effect of the 1997 reform. The evidence is suggestive, and some alternative interpretations of the patterns in the data, shown in the plot below, cannot be excluded at the moment. While a peak-and-slump pattern as in Miller (2009) would have been much stronger evidence supporting the success of the reform at deterring corruption, we cannot exclude that the drop in prosecutions is simply due to a general worsening in detection. Although we deem this unlikely in the light of the general political climate of the time, we need more and better data to support our interpretation. Still, claims that the reform did not have an effect appear not supported by the data.
Figure 1. Change in Corruption Prosecutions before and after law reform in 1997
Source: Perrotta-Berlin and Spagnolo (2015).
More to be done
A case study analysis is under way to corroborate and help the interpretation of these preliminary findings. We will analyze in depth a stratified random sample of prosecution case files between 1980 and 2010. Given that we sample a given number of cases, in this part of the analysis we cannot gain any insight about the incidence of bribery in general. We can instead observe the impact of the legislative reform on specific details of the corrupt behavior, and the mechanisms through which this behavior occurs or is deterred. In particular, we will be able to distinguish between cases of extortionary (harassment) bribes and bribes paid to obtain illegitimate benefits. Moreover, this will allow us to shed light on whether and how leniency and asymmetric punishment were applied in practice. The details of the case files might even allow us to gain insight into how the bribe-size and the value of corrupt deals evolved through the reform and even the selection into bureaucracy.
Conclusion
One-sided leniency, conditional on reporting an act first, or unconditional, as when bribe giving is depenalized, may be powerful corruption deterrence instruments if well designed and implemented in the right environment, but may also have negative effects. It has been argued that these instruments have been ineffective in China, after they were reformed in 1997, however, without data supporting the claim. Part of the reason lies in the difficulty to obtain good data on corruption. Another obstacle is the subtlety of interpreting them when they relate only to detected and convicted cases, rather than to the whole population of corruption cases.
We cannot solve completely the issue of data quality, as we also need to rely on official reports of counts of corruption cases. However limited, the exercise performed on aggregated data clearly shows that the 1997 Criminal Law reform did have an effect, consistent with increased corruption deterrence. To further support this finding we will collect and analyze micro-data from a randomized sample of these cases. This will allow us to isolate at a higher level of detail the changes in criminal behavior, reporting behavior and prosecution activity, and link them to the details of the legal reform to highlight the mechanisms at work.
China is home to a sixth of humanity, and currently undergoing a massive crackdown on corruption. Whatever we can learn about the effectiveness of their past and present anti-corruption policies is likely to have considerable welfare effects. Moreover, the 1997 reform was the object of a policy debate, and comments on its effectiveness came without data to support them. We believe our effort to use data to shed light on what this reform actually changed will be a valuable input to further research and policy discussion on this important topic.
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References
- Abbink, K., U. Dasgupta, L. Gangadharan, and T. Jain. “Let-ting the Briber Go Free: An Experiment on MitigatingHarassment Bribes.” Journal of Public Economics, 111,2014, 17–28.
- Basu, K. “Why, for a Class of Bribes, the Act of Giv-ing a Bribe Should Be Treated as Legal.” WorkingPaper 172011 DEA, Ministry of Finance, Governmentof India, 2011
- Bigoni, M., S.-O. Fridolfsson, C. LeCoq, and G. Spagnolo.“Fines, Leniency and Rewards in Antitrust.” RANDJournal of Economics, 43, 2012a, 368–90.
- Bigoni, M., S.-O. Fridolfsson, C. LeCoq, and G. Spagnolo.. “Trust and Deterrence.”. Journal of Law, Economics, and Organization (2015)
- Buccirossi, P., and G. Spagnolo. “Leniency Policies and Ille-gal Transactions.” Journal of Public Economics, 90,2006, 1281–97.
- Buccirossi, P., Marvão, C. M. P., & Spagnolo, G. (2015). Leniency and Damages. Available at SSRN 2566774.
- Dufwenberg, M. and Spagnolo, G., Legalizing Bribe Giving (April 2015). Economic Inquiry, Vol. 53, Issue 2, pp. 836-853, 2015.
- Li, X. Guest post: bribery and the limits of game theory – the lessons from China. http://blogs.ft.com/beyond-brics/2012/05/01/guest-post-bribery-and-the-limits-of-game-theory-the-lessons-from-china/, 2012. Accessed: 2015-05-20.
- Miller, N. H. Strategic leniency and cartel enforcement. The American Economic Review, pages 750–768, 2009.
- Perrotta Berlin, M. and G. Spagnolo, Leniency, Asymmetric Punishment and Corruption: Evidence from China, SITE Working Paper, 2015 (forthcoming)