In a global trading landscape that is being increasingly influenced by protectionist narratives, the approval of the landmark European Union-Canada trade deal Comprehensive Economic and Trade Agreement (Ceta) by the European Parliament comes as a breath of fresh air. Trade between the two economies amounts to about $63 billion presently, and reports say Ceta could increase this by 20% to as much as $76 billion.
Realizing these gains from trade would require dismantling not just tariffs but also non-tariff barriers as envisioned in Ceta. While the former has finally been voted upon in the EU parliament and about to be enforced after more than seven years of negotiation, the latter still hangs in the balance. Reducing non-tariff barriers would require ratification by EU member states, a task that is both formidable and time-consuming. Last year, the tiny Wallonia region of Belgium, with a population of about 3.5 million, held the entire deal hostage to its concerns about the loss of welfare due to trade. Foreign competition induced by Ceta was particularly feared to hurt Wallonia’s farmers, who were increasingly facing higher production costs in their region. To be sure, such concerns are legitimate and are shared by a host of countries, including the US.
But that narrative fails to take into account the huge welfare gains that accrue to consumers of cheaper imports. A 2016 paper by economists Holger Breinlich, Swati Dhingra, and Gianmarco Ottaviano of the London School of Economics analysed the effects of free trade agreements (FTAs) negotiated by the EU in the past two decades. They concluded that these agreements not only improved the quality of the UK’s imports by 26%, but also lowered the quality-adjusted price of those imports by 19%. For EU-12 countries, which include Belgium, FTAs enhanced the quality of imported goods by 28%, while reducing the quality-adjusted prices by 11%.
In value terms, cheap imports resulted in savings of as much as $5.6 billion for UK consumers every year. Furthermore, the authors also predict that treaties such as the Transatlantic Trade and Investment Partnership between the EU and the US could save EU consumers $4.45 billion, while the Economic Partnership Agreement between the EU and Japan could save them $2.23 billion by way of lower import prices.
In simpler terms, trade has a pro-poor bias, and any barriers to trade can quickly degenerate into barriers to reducing poverty. That is not to downplay the distributional consequences of trade or engage in trade fundamentalism. Trade hurts uncompetitive businesses and causes unemployment. But as long as the losers are compensated from the aggregate welfare gains resulting from trade, there is a strong case to be made in favour of liberalizing restrictions. This compensation should be in the form of robust safety nets—such as unemployment insurance benefits or income support payments—that are combined with skilling programmes to retrain displaced workers for new employment opportunities.
There could also be a legitimate argument in favour of imposing anti-dumping or countervailing duties on certain items if the cheap import happens to be a result of market distortions created by the foreign trade partner in its home country. In its high growth years, for example, China witnessed heavy state-led investments in its steel industry. This led to industrial overcapacity in the subsequent low growth years when domestic demand faded. Consequently, Chinese producers engaged in price discrimination by exporting steel to foreign markets at prices far lower than those prevailing domestically. The importing countries naturally witnessed damage to their domestic steel industries, but not necessarily due to their own inefficiencies or weaknesses. They lost out owing to market distortions or failures induced by their foreign trade partner’s state policy. This could justify appropriate domestic measures.
The problem with such measures, however, is that it is often difficult to distinguish clearly between cheap imports induced by market distortions and those taking place as a result of genuine comparative cost competitiveness of the foreign producers. And the result is a flagrant misuse of anti-dumping measures to thwart even genuine imports. A 2015 working paper by economists Chad Bown and Rachel McCulloch of the European University Institute found that even though anti-dumping measures in the 1980s were originally employed to prevent anti-competitive behaviour, they gradually ended up being misused to create collusion and cartelization by domestic producers.
Given their potential for misuse, protectionist measures should be avoided or limited to exceptional situations only. Where such effects are unclear, trade should be allowed to take its own course
Darknet, also known as dark web or darknet market, refers to the part of the internet that is not indexed or accessible through traditional search engines. It is a network of private and encrypted websites that cannot be accessed through regular web browsers and requires special software and configuration to access.
The darknet is often associated with illegal activities such as drug trafficking, weapon sales, and hacking services, although not all sites on the darknet are illegal.
Examples of darknet markets include Silk Road, AlphaBay, and Dream Market, which were all shut down by law enforcement agencies in recent years.
These marketplaces operate similarly to e-commerce websites, with vendors selling various illegal goods and services, such as drugs, counterfeit documents, and hacking tools, and buyers paying with cryptocurrency for their purchases.
Anonymity: Darknet allows users to communicate and transact with each other anonymously. Users can maintain their privacy and avoid being tracked by law enforcement agencies or other entities.
Access to Information: The darknet provides access to information and resources that may be otherwise unavailable or censored on the regular internet. This can include political or sensitive information that is not allowed to be disseminated through other channels.
Freedom of Speech: The darknet can be a platform for free speech, as users are able to express their opinions and ideas without fear of censorship or retribution.
Secure Communication: Darknet sites are encrypted, which means that communication between users is secure and cannot be intercepted by third parties.
Illegal Activities: Many darknet sites are associated with illegal activities, such as drug trafficking, weapon sales, and hacking services. Such activities can attract criminals and expose users to serious legal risks.
Scams: The darknet is a hotbed for scams, with many fake vendors and websites that aim to steal users’ personal information and cryptocurrency. The lack of regulation and oversight on the darknet means that users must be cautious when conducting transactions.
Security Risks: The use of the darknet can expose users to malware and other security risks, as many sites are not properly secured or monitored. Users may also be vulnerable to hacking or phishing attacks.
Stigma: The association of the darknet with illegal activities has created a stigma that may deter some users from using it for legitimate purposes.
AI, or artificial intelligence, refers to the development of computer systems that can perform tasks that would normally require human intelligence, such as recognizing speech, making decisions, and understanding natural language.
Virtual assistants: Siri, Alexa, and Google Assistant are examples of virtual assistants that use natural language processing to understand and respond to users’ queries.
Recommendation systems: Companies like Netflix and Amazon use AI to recommend movies and products to their users based on their browsing and purchase history.
Efficiency: AI systems can work continuously without getting tired or making errors, which can save time and resources.
Personalization: AI can help provide personalized recommendations and experiences for users.
Automation: AI can automate repetitive and tedious tasks, freeing up time for humans to focus on more complex tasks.
Job loss: AI has the potential to automate jobs previously performed by humans, leading to job loss and economic disruption.
Bias: AI systems can be biased due to the data they are trained on, leading to unfair or discriminatory outcomes.
Safety and privacy concerns: AI systems can pose safety risks if they malfunction or are used maliciously, and can also raise privacy concerns if they collect and use personal data without consent.