Auswahl der wissenschaftlichen Literatur zum Thema „Trade Policy Uncertainty“

We explore conditions under which trade agreements can provide gains by reducing trade policy uncertainty. Given the degree of income risk aversion, this is more likely when economies are more open, export supply elasticities are lower, and economies more specialized. Governments have stronger incentives to sign trade agreements when the trading environment is more uncertain. As exogenous trade costs decline, the gains from reducing tariff uncertainty become more important relative to reducing average tariff levels. We also develop a simple “sufficient statistic” approach to quantify the gains from managing trade policy uncertainty, and examine the impact of ex ante investments on such gains. (JEL D81, F13)

This paper uses the economic policy uncertainty and total import volume of 20 countries including the United States and China and the European Union from 2007 to 2021 and related data, and uses a fixed-effect model to study the impact of economic policy uncertainty on import trade. The results show that internal economic policy uncertainty significantly inhibits import trade, while global economic policy uncertainty has no significant impact on import trade. Maintaining good international relations with other countries and avoiding trade frictions is a Sensible way to promote import trade.

This study uses a nonlinear stochastic matrix for an in-depth analysis of the association between international trade growth and environmental change. First, for a class of uncertain stochastic nonlinear time-lag systems, this study investigates its time-lag-related robust stochastic stabilization problem. A memory-free state feedback controller for the system is then obtained to ensure the effectiveness of the system performance. This makes the system more general and the corresponding theoretical results less conservative. Finally, numerical examples are given to further verify the validity and feasibility of the results. The “tariff measure” based on the magnitude of adverse changes in trade policy is not an accurate measure of trade policy uncertainty; the stochastic volatility method measures trade policy uncertainty by including tariff fluctuations that have been communicated in advance in the trade policy uncertainty indicator and fail to identify the different commodities that occur during the current trade friction. The trade policy uncertainty index constructed through textual analysis of newspapers can better reflect the trade policy uncertainty during this trade friction between China and the United States, and the rich time-varying nature can also reflect the alternating changes of tension and détente in economic and trade relations over some time. The analysis of the mechanism reveals that exporters have fewer emission reduction facilities than nonexporters but significantly lower energy consumption intensity for coal and water than nonexporters, reasoning that the mechanism by which exporters are more environmentally friendly than nonexporters lies in their cleaner energy use mix. Following the conclusions of this study, relevant policy recommendations are put forward, specifically the use of more efficient energy sources in the production process and more investment in energy efficiency and emission reduction to combat pollution.

Since the subprime crisis, the U.S. has begun to adjust its international trade policies due to the worldwide economic slowdown, leaving its trading partners facing great uncertainty in trade policy. In this study, we developed a panel model to empirically analyze the impact of U.S. trade policy uncertainty on the extensive margin, intensive margin, price margin, and quantity margin of Chinese exports of U.S. goods. We found that U.S. trade policy uncertainty is also a trade barrier for China’s export trade. The extensive margin, intensive margin, price margin, and quantity margin of Chinese exports to the U.S. are all adversely connected with U.S. trade policy uncertainty. The increase in U.S. trade policy uncertainty significantly inhibits the increase in the extensive margin, intensive margin, and quantity margin of China’s exports to America, and the degree of inhibition of the quantity margin is five times that of the extensive margin. Increased U.S. trade policy uncertainty also restrains the increase in the price margin of Chinese exports to America, but this is not statistically significant. In this study, we emphasize the significant impact that U.S. trade policy uncertainty has had on the trade margins of Chinese exports of goods to America. To stabilize China’s exports to the United States, China should increase support for export enterprises’ technological R&D and innovation, expand bilateral or multilateral free trade agreements with other countries, and so on.

PurposeThis study aims to empirically examine how economic policy uncertainty emanating from three major global economic blocks (the US, the Chinese and the European Union) and volatility in global oil prices influence international trade.Design/methodology/approachThe study uses quarterly data spanning the period between 1995 and 2014 in an autoregressive distributed lag framework.FindingsThis study finds that economic policy uncertainty conditions associated with the US and the Chinese economies tend to have significant negative or constraining impact on key components of international trade. Further analysis suggests that between the two leading economies (the US and the Chinese economies), economic policy uncertainty emanating from the US economy tend to have much more constraining impact on dynamics of international trade than the Chinese economy all things being equal.Practical implicationsThis study’s findings carry significant strategic planning and policy implications for international trade dependent firms or corporations and economies. For instance, for multi-national corporations or firms whose products and services depend heavily on cross-border trade, understanding and taking into consideration prevailing economic policy dynamics emanating from the US and the Chinese economies in product and services demand forecast, and other strategic moves could be critical in minimizing potential adverse effects on projected performance or growth targets.Originality/valueThe uniqueness of this study’s approach stems from its assessment of how perception of uncertainty among economic agents about economic policies originating from three noted global economic blocks impacts international trade. In other words, instead of traditional factors or conditions surmised to influence variability in trend associated with international trade found in related studies, this study rather examines how perceptions of uncertainty about prevailing or yet to be enacted economic policy within specific global economic block impacts international trade.

The drivers of CO2 emissions are a widely studied subject of great importance to both individual countries and the global community. However, the inclusion of a quantitative measure of political uncertainty, national and global, has until now been largely overlooked. We investigate how geopolitical uncertainty (GPU) and income interact with CO2 emissions using a panel quantile regression approach for a set of 63 nations over the period 1985-2014. Our key findings are; (i) a consistent negative (positive) relation between global (local) uncertainty and the different CO2 emission distribution levels, (ii) the relation between uncertainty and emissions is heterogeneous across different income groups, (iii) clear and consistent evidence for the Environmental Kuztnet Curve hypothesis with respect to uncertainty, (iiii) when deciding on environmental policy, it is of great importance to consider political uncertainty and whether to use a local or global measure.

This dissertation is a collection of three essays on strategic trade policy. The main purpose of this research is to make contributions to the strategic trade literature by dealing with some of its interesting and important issues. The first essay extends the well-known Brander-Spencer (1985) model, by considering market uncertainty, endogenizing firms' choice of strategic variables, and introducing a quadratic export tax/subsidy scheme; and investigates the interrelationship between trade policies and market competition. It is shown that firms are not indifferent between setting prices and setting quantities in an uncertain environment. The quadratic export tax/subsidy scheme is proved superior to the linear export tax/subsidy scheme because the former has the unique ability to influence the domestic firm's choice of strategic variables and therefore to affect the market conduct in favour of the domestic country. The second essay explores an incomplete information version of the Brander-Spencer (1985) model, in which the domestic firm's production cost is private in-formation. This model has the distinguishing feature that it contains a mixture of screening and signalling problems. Because of this, policy makers are confronted by twin conflicting policy objectives: choosing between an information revealing policy menu and an information concealing uniform policy. We prove that the policy menu is preferred to the uniform policy in quantity competition while the opposite is true in price competition. In essay three, we examine the implications of credit rationing for international trade. Development and production of new products often involves uncertainty (e.g. R&D uncertainty and demand uncertainty), which could lead to credit rationing. We find that the presence of credit rationing may give partial explanation for the indeterminacy of the pattern of trade between two similar countries. When credit is rationed, two-way trade is less likely to occur.

The needs of the free trade regime and governments' legitimate regulatory aims in the area of public health protection conflict. Government health measures create barriers to free trade and are thus disciplined by the trade regime. This conflict is addressed in the rules of the World Trade Organization, in the Agreement on the Application of Sanitary and Phytosanitary Measures. This Agreement uses science to mediate the conflict. The reason for the reliance on science is the view that it provides a neutral, universally-valid discipline and that thus the results of testing health measures for scientific validity would be acceptable to both parties in a dispute. This uncritical approach towards science is called into question. An analysis of the relevant science-based disciplines of the SPS Agreement and their interpretation in WTO dispute settlement shows the flaws in this system. A re-evaluation of the WTO rules governing health regulation is called for.
Law
LL.M.

The needs of the free trade regime and governments' legitimate regulatory aims in the area of public health protection conflict. Government health measures create barriers to free trade and are thus disciplined by the trade regime. This conflict is addressed in the rules of the World Trade Organization, in the Agreement on the Application of Sanitary and Phytosanitary Measures. This Agreement uses science to mediate the conflict. The reason for the reliance on science is the view that it provides a neutral, universally-valid discipline and that thus the results of testing health measures for scientific validity would be acceptable to both parties in a dispute. This uncritical approach towards science is called into question. An analysis of the relevant science-based disciplines of the SPS Agreement and their interpretation in WTO dispute settlement shows the flaws in this system. A re-evaluation of the WTO rules governing health regulation is called for.
Law
LL.M.

The United States announced plans to impose tariffs and quotas on her imports of certain commodities, notably iron, steel and aluminum, and on imports from certain countries, including those from China, in early 2018. These and counter announcements has been considered as the start of global trade wars. Even before that, there has been a significant slowdown in the growth of world trade in recent years. In the three decades before 2011, annual world trade recorded a growth of about 6%. This was twice as high as world GDP growth, implying an income (GDP) elasticity of trade at around 2. Between 2011 – 2016, the income elasticity of trade has fallen to below 1, on average. While the recent poor performance of global trade has been attributed to these structural and cyclical factors, this paper argues that the rise in both price uncertainty, demand uncertainty and policy uncertainty have and will have a significant effect on trade growth. Price uncertainty is reflected in fluctuations in real exchange rates, commodity prices and manufacturing prices. Demand uncertainty, on the other hand, is reflected by growth variability in time and among countries. Policy uncertainty can be traced in protectionist measures.

This paper aims to assess economic convergence in the BIMSTEC organization initiated by seven South and SouthEast Asian countries. Its current state of growth is compared with empirically formulated growth model to determine its institutional efficiency i.e., strong or weak. GDP growth is considered proxy for economic security to analyze the result of the crossborder economic integration. The analysis covers the period of 19982018, a time series interval of 21 years. Linear regression equation shows the existence of convergence and convergence among the countries however, the organization has faced uncertainty and low significance on its economic effectiveness due to increased militant insurgencies in the region and other laggard policy implications. In sum, the main findings of this paper highlight (i) implications of opening crossborder trade routes through free trade agreement and (ii) existence of economic convergence in the member states. This therefore facilitates better trade, increased employment, tourism, investment and other macroeconomic successes within the bordersharing Asian neighbors.

Intelligent robots frequently need to explore the objects in their working environments. Modern sensors have enabled robots to learn object properties via perception of multiple modalities. However, object exploration in the real world poses a challenging trade-off between information gains and exploration action costs. Mixed observability Markov decision process (MOMDP) is a framework for planning under uncertainty, while accounting for both fully and partially observable components of the state. Robot perception frequently has to face such mixed observability. This work enables a robot equipped with an arm to dynamically construct query-oriented MOMDPs for multi-modal predicate identification (MPI) of objects. The robot's behavioral policy is learned from two datasets collected using real robots. Our approach enables a robot to explore object properties in a way that is significantly faster while improving accuracies in comparison to existing methods that rely on hand-coded exploration strategies.

Abstract In agricultural and industrial equipment, both new and remanufactured systems are often available for warranty coverage. In such cases, it may be challenging for equipment manufacturers to properly trade-off between the system reliability and the cost associated with a replacement option (e.g., replace with a new or remanufactured system). To address this problem, we present a reliability-informed life-cycle warranty cost (LCWC) analysis framework that enables equipment manufacturers to evaluate different warranty policies. These warranty policies differ in whether a new or remanufactured system is used for replacement in the case of product failure. The novelty of this LCWC analysis framework lies in its ability to incorporate real-world field reliability data into warranty policy assessment using probabilistic warranty cost models that consider multiple life cycles. First, the reliability functions for the new and remanufactured systems are built as the time-to-failure distributions that provide the best-fit to the field reliability data. Then, these reliability functions and their corresponding warranty policies are used to build the LCWC models according to the specific warranty terms. Finally, Monte Carlo simulation is used to propagate the time-to-failure uncertainty of each system, modeled by its reliability function, through each LCWC model to produce a probability distribution of the LCWC. The effectiveness of the proposed reliability-informed LCWC analysis framework is demonstrated with a real-world case study on a transmission used in some agricultural equipment.

According to estimates and analyses by the international community of economic analysts, the medical crisis generated by the Covid-19 pandemic will induce a major economic and financial crisis worldwide which, in conjunction with the current geopolitical situation, characterized by a high degree of uncertainty (e.g. strategic economic confrontation between the US and China, the position of force adopted by the Russian Federation), will affect production and supply chains, amplify the phenomenon of the adoption of trade policies of a protectionist nature, and, indirectly, will significantly affect national defense budgets. In this fluid geopolitical context, characterized by insecurity and systemic instability, a strategic rethink and recalibration of defence policies can be predicted in a new context, defined by the multipolar competition and the asymmetry of geopolitical geometry, the conflict between civilizational models (competition between democracy vs. autocratic/totalitarian political regimes), to the detriment of regional and international collective security arrangements. Changing government priorities generated by the pandemic crisis generated by Covid-19 may lead to a reduction in budgets for military endowment programs. Most governments allocate about 2% of GDP annually to the defence sector. Given the pandemic generated by Covid-19, there is a risk that some states will significantly reduce the budget allocated to the defence industry in order to increase the budgets for health systems, given the need to expand hospitals, as well as the purchase of medical equipment and services. In Romania, the topic of tools and opportunities that may be able to ensure the improvement of the effects and overcoming the economic crisis is currently being discussed through active economic measures, including in the field of the defence industry. In Romania, however, the path from debate to public policy and strategy assumed and applied is traditionally long and hard, requiring more pragmatism in addressing strategic economic issues.

ANSI/NCSL Z540.3-2006 and ISO/IEC 17025:2005 are voluntary consensus standards which prescribe requirements for the calibration of measuring and test equipment and for the technical competency of the performing laboratories. Many agencies in the U.S. which are part of, or regulated by, the Federal Government are required to use instruments which have been calibrated in accordance with one or both of these standards. The National Technology Transfer and Advancement Act (NTTAA) of 1995 compels all federal agencies to use technical standards that are developed by consensus standards bodies, in lieu of "government-unique" standards. ISO 17025 and ANSI Z540.3 have evolved over a half-century of metrological advancement, drawing upon expertise in the public and private sector. They are now supported by a mature infrastructure that facilitates mutual recognition and global trade, ensuring calibrations are accepted worldwide. However, some federal agencies and regulatory bodies in the U.S. have not yet adopted these standards. Calibrations are routinely performed on instruments, utilized in some government-regulated industries, which may not conform to these requirements. This paper discusses risks imparted to products and services produced in such environments. Particular focus is given to the Food and Drug Administration's (FDA) regulation of calibration requirements in the Quality System Regulation (QSR) found in Title 21 of the Code of Federal Regulations (CFR). Currently, a paucity of official guidance exists with respect to what constitutes an acceptable calibration program in medical device and pharmaceutical industries. Ambiguities persist due to lack of agreement upon voluntary consensus standards such as ISO 17025 and ANSI Z540.3. Fundamental requirements such as traceability, measurement uncertainty, measurement decision-rules, as well as basic metrological definitions are ill-defined in the CFR. The objective of this paper is to provide relevant background information and to encourage constructive dialogue between government agencies, standards writing committees, industry partners, and third party assessment/accreditation bodies. Cooperation of this type is consistent with public law and White House policy objectives. Ultimately, such dialogue may foster agreement on the use of these voluntary consensus standards for calibration in regulated industries, resulting in improved quality and reduced risk to consumers and patients.

Abstract The Petroleum Working Group (PWG) of the United Nations Economic Commission for Europe (UNECE) has developed the Petroleum Resource Specifications and Guidelines (PRSG) to facilitate the application of the United Nations Framework Classification for Resources (UNFC) for evaluating and classifying petroleum projects. The UNFC was developed by the Expert Group on Resource Management (EGRM) and covers all resource sectors such as minerals, petroleum, renewable energy, nuclear resources, injection projects, anthropogenic resources and groundwater. It has a unique three- dimensional structure to describe environmental, social and economic viability (E-axis), technical feasibility and maturity (F-axis) and degree of confidence in the resource estimates (G-axis). The UNFC is fully aligned to holistic and sustainable resource management called for by the 2030 Agenda for Sustainable Development (2030 Agenda). UNFC can be used by governments for integrated energy planning, companies for developing business models and the investors in decision making. Internationally, all classification systems and their application continue to evolve to incorporate the latest technical understanding and usage and societal, government and regulatory expectations. The PRSG incorporates key elements from current global petroleum classification systems. Furthermore, it provides a forward-thinking approach to including aspects of integrity and ethics. It expands on the unique differentiator of the UNFC to integrate social and environmental issues in the project evaluation. Several case studies have been carried out (in China, Kuwait, Mexico, Russia, and Uganda) using UNFC. Specifically, PRSG assists in identifying critical social and environmental issues to support their resolution and development sustainably. These issues may be unique to the country, location and projects and mapped using a risk matrix. This may support the development of a road map to resolve potential impediments to project sanction. The release of the PRSG comes at a time of global economic volatility on a national and international level due to the ongoing impact and management of COVID-19, petroleum supply and demand uncertainty and competing national and international interests. Sustainable energy is not only required for industries but for all other social development. It is essential for private sector development, productive capacity building and expansion of trade. It has strong linkages to climate action, health, education, water, food security and woman empowerment. Moreover, enduring complex system considerations in balancing the energy trilemma of reliable supply, affordability, equity, and social and environmental responsibility remain. These overarching conditions make it even more essential to ensure projects are evaluated in a competent, ethical and transparent manner. While considering all the risks, it is also critical to reinforce the positive contribution a natural resource utilization project provides to society. Such an inquiry can focus on how the project contributes to the quality of life, environment, and the economy – the people, planet, and prosperity triad. Such an approach allows consistent, robust and sustainable investment decision making and energy policy development.

Deep Reinforcement Learning (Deep-RL) has received considerable attention in recent years due to its ability to make an agent learn how to take optimal control actions, given rich observation data via the maximization of a reward function. Future space missions will need new on-board autonomy capabilities with increasingly complex requirements at the limits of the vehicle performance. This justifies the use of machine learning based techniques, in particular reinforcement learning in order to allow explore the edge of the performance trade-off space. The guidance and control systems development for Reusable Launch Vehicles (RLV) can take advantage of reinforcement learning techniques for optimal adaption in the face of multi-objective requirements and uncertain scenarios. In this work, a Deep-RL algorithm is used to train an actor-critic agent to simultaneously control the engine thrust magnitude and the two TVC gimbal angles to land a RLV in 6-DoF simulation. The design followed an incremental approach, progressively augmenting the number of degrees of freedom and introducing more complexity factors such as non-linearity in models. Ultimately, the full 6-DoF problem was addressed using a high fidelity simulator that includes a nonlinear actuator model and a realistic vehicle aerodynamic model. Starting from an initial vehicle state along a reentry trajectory, the problem consists of precisely land the RLV while ensuring system requirements satisfaction, such as saturation and rate limits in the actuation, and aiming at fuel consumption optimality. The Deep Deterministic Policy Gradient (DDPG) algorithm was adopted as candidate strategy to allow the design of an integrated guidance and control algorithm in continuous action and observation spaces. The 1-DoF and 2-DoF scenarios considered allowed to perform hyperparameter sensitivity analyses, as well as to better understand how to shape the reward function in dealing with the performance trade-off space. Moreover, the inclusion of the actuation model, which also considers rate limiters, was shown to considerably hinder the design. This challenge motivated the redefinition of the observation state and the type of output that the Neural Network (NN) agent provides. The results obtained are very satisfactory in terms of landing accuracy and fuel consumption. These results were also compared to a more classical and industrially used solution, due to its capability to yield satisfactory landing accuracy and fuel consumption, composed of a successive convexification guidance and a PID controller tuned independently for the non-disturbed nominal scenario. This comparison led to the conclusion that the Deep-RL yields, for this benchmark, a better landing position accuracy. A 1000-shot Monte Carlo (MC) campaign was also performed, leading to a 97% success rate in terms of requirements satisfaction, for a scenario with wind effects not considered during the Deep-RL training. Furthermore, a reachability analysis was also performed to access the stability and robustness of the closed-loop system composed by the integrated guidance and control NN, trained for the 1-DoF scenario, and the RLV dynamics. Taking into account the fidelity of the benchmark adopted and the results obtained, this approach is deemed to have a significant potential for further developments and ultimately space industry applications, such as In-Orbit Servicing (IOS) and Active Debris Removal (ADR), that also require a high level of autonomy. The paper will describe the design, implementation, and validation of the proposed approach, presenting some of the very promising results obtained, which demonstrate the capability to successfully address the RLV landing problem with this type of technique.

This paper examines the impact of global shocks on monetary policy transmission in 24 emerging market economies. Using panel local projections over the period 2000 to 2022, the results show that tighter United States monetary policy, higher global financial market uncertainty, and worsening global climate change impair the transmission of monetary policy to inflation and output. Higher financial development in emerging market economies can partially offset the disruption, while more open capital accounts and trade can amplify the impact of global shocks.

This paper investigates the relationship between the views expressed in the minutes of the meetings of the Central Bank of Brazil’s Monetary Policy Committee (COPOM) and the real economy. It applies various computational linguistic machine learning algorithms to construct measures of the minutes of the COPOM. First, we create measures of the content of the paragraphs of the minutes using Latent Dirichlet Allocation (LDA). Second, we build an uncertainty index for the minutes using Word Embedding and K-Means. Then, we combine these indices to create two topic-uncertainty indices. The first one is constructed from paragraphs with a higher probability of topics related to “general economic conditions”. The second topic-uncertainty index is constructed from paragraphs that have a higher probability of topics related to “inflation” and the “monetary policy discussion”. Finally, we employ a structural VAR model to explore the lasting effects of these uncertainty indices on certain Brazilian macroeconomic variables. Our results show that greater uncertainty leads to a decline in inflation, the exchange rate, industrial production and retail trade in the period from January 2000 to July 2019.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.

The performance of supply chains used to be mainly the concern of academics and professionals who studied the potential efficiencies and risks associated with this aspect of globalisation. In 2021, major disruptions in this critical sector of our economies are making headlines and attracting the attention of policy makers around the world. Supply chain bottlenecks create shortages, fuel inflation, and undermine economic recovery. This report provides a transversal and multidisciplinary analysis of the challenges and opportunities regarding data interoperability and data sharing as they relate to the ‘Great Lakes - St. Lawrence Seaway Trade Corridor’ (GLSLTC)’s intermodal transportation and trade data strategy. The size and scope of this trade corridor are only matched by the complexity of its multimodal freight transportation systems and growing urbanization on both sides of the Canada-US border. This complexity is exacerbated by the lack of data interoperability and effective collaborations between the different stakeholders within the various jurisdictions and amongst them. Our analytical work relies on : 1) A review of the relevant documentation on the latest challenges to supply chains (SC), intermodal freight transport and international trade, identifying any databases that are to be used.; 2) A comparative review of selected relevant initiatives to give insights into the best practices in digital supply chains implemented in Canada, the United States, and the European Union.; 3) Interviews and discussions with experts from Transport Canada, Statistics Canada, the Canadian Centre on Transportation Data (CCTD) and Global Affairs Canada, as well as with CIRANO’s research community and four partner institutions to identify databases and data that they use in their research related to transportation and trade relevant data availabilities and methodologies as well as joint research opportunities. Its main findings can be summarized as follow: GLSLTC is characterized by its critical scale, complexity, and strategic impact as North America’s most vital trade corridor in the foreseeable further intensification of continental trade. 4% of Canadian GDP is attributed to the Transportation and Logistics sector (2018): $1 trillion of goods moved every year: Goods and services imports are equivalent to 33% of Canada’s GDP and goods and services exports equivalent to 32%. The transportation sector is a key contributor to the achievement of net-zero emissions commitment by 2050. All sectors of the Canadian economy are affected by global supply chain disruptions. Uncertainty and threats extend well beyond the COVID-19 Pandemic. “De-globalization” and increasing supply chains regionalization pressures are mounting. Innovation and thus economic performance—increasingly hinges on the quantity and quality of data. Data is transforming Canada’s economy/society and is now at the center of global trade “Transport data is becoming less available: Canada needs to make data a priority for a national transportation strategy.” * “How the Government of Canada collects, manages, and governs data—and how it accesses and shares data with other governments, sectors, and Canadians—must change.”