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Assessing the current state of the economy and forecast the economic outlook in the next few quarters are important inputs for policymakers. This paper presents a suite of models with an integrated approach to forecast Cambodia’s economy in the current and next few quarters. First, we estimate historical quarterly GDP using information extracted from high-frequency indicators to construct quarterly nowcasting model. Second, we forecast current economic activities using a high-frequency data such as credit, export, tourist arrival, foreign reserves, and trading partner’s GDP. Third, we present inflation forecasting models for Cambodia. Fourth, the paper present a vector autoregression model to forecast Cambodia’s GDP in the next few quarters using global forecasts of China’s and US’s economy as well as oil and rice price. This paper showcase how high-frequency data set can be utilized in assessing current economic activities in countries with limited and lagged data.
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
We study the properties of the IMF-WEO estimates of real-time output gaps for countries in the euro area as well as the determinants of their revisions over 1994-2017. The analysis shows that staff typically saw economies as operating below their potential. In real time, output gaps tend to have large and negative averages that are largely revised away in later vintages. Most of the mis-measurement in real time can be explained by the difficulty in predicting recessions and by overestimation of the economy’s potential capacity. We also find, in line with earlier literature, that real-time output gaps are not useful for predicting inflation. In addition, countries where slack (and potential growth) is overestimated to a larger extent primary fiscal balances tend to be lower and public debt ratios are higher and increase faster than projected. Previous research suggests that national authorities’ real-time output gaps suffer from a similar bias. To the extent these estimates play a role in calibrating fiscal policy, over-optimism about long-term growth could contribute to excessive deficits and debt buildup.
Timely data availability is a long-standing challenge in policy-making and analysis for low-income developing countries. This paper explores the use of Google Trends’ data to narrow such information gaps and finds that online search frequencies about a country significantly correlate with macroeconomic variables (e.g., real GDP, inflation, capital flows), conditional on other covariates. The correlation with real GDP is stronger than that of nighttime lights, whereas the opposite is found for emerging market economies. The search frequencies also improve out-of-sample forecasting performance albeit slightly, demonstrating their potential to facilitate timely assessments of economic conditions in low-income developing countries.
In 2013, the World Bank Group announced two goals that would guide its operations worldwide. First is the eradication of chronic extreme poverty bringing the number of extremely poor people, defined as those living on less than 1.25 purchasing power parity (PPP)†“adjusted dollars a day, to less than 3 percent of the world’s population by 2030.The second is the boosting of shared prosperity, defined as promoting the growth of per capita real income of the poorest 40 percent of the population in each country. In 2015, United Nations member nations agreed in New York to a set of post-2015 Sustainable Development Goals (SDGs), the first and foremost of which is the eradication of extreme poverty everywhere, in all its forms. Both the language and the spirit of the SDG objective reflect the growing acceptance of the idea that poverty is a multidimensional concept that reflects multiple deprivations in various aspects of well-being. That said, there is much less agreement on the best ways in which those deprivations should be measured, and on whether or how information on them should be aggregated. Monitoring Global Poverty: Report of the Commission on Global Poverty advises the World Bank on the measurement and monitoring of global poverty in two areas: What should be the interpretation of the definition of extreme poverty, set in 2015 in PPP-adjusted dollars a day per person? What choices should the Bank make regarding complementary monetary and nonmonetary poverty measures to be tracked and made available to policy makers? The World Bank plays an important role in shaping the global debate on combating poverty, and the indicators and data that the Bank collates and makes available shape opinion and actual policies in client countries, and, to a certain extent, in all countries. How we answer the above questions can therefore have a major influence on the global economy.
This edition of the biennial Poverty and Shared Prosperity report brings sobering news. The COVID-19 (coronavirus) pandemic and its associated economic crisis, compounded by the effects of armed conflict and climate change, are reversing hard-won gains in poverty reduction and shared prosperity. The fight to end poverty has suffered its worst setback in decades after more than 20 years of progress. The goal of ending extreme poverty by 2030, already at risk before the pandemic, is now beyond reach in the absence of swift, significant, and sustained action, and the objective of advancing shared prosperity—raising the incomes of the poorest 40 percent in each country—will be much more difficult. Poverty and Shared Prosperity 2020: Reversals of Fortune presents new estimates of COVID-19's impacts on global poverty and shared prosperity. Harnessing fresh data from frontline surveys and economic simulations, it shows that pandemic-related job losses and deprivation worldwide are hitting already poor and vulnerable people hard, while also shifting the profile of global poverty to include millions of 'new poor.' Original analysis included in the report shows that the new poor are more urban, better educated, and less likely to work in agriculture than those living in extreme poverty before COVID-19. It also gives new estimates of the impact of conflict and climate change, and how they overlap. These results are important for targeting policies to safeguard lives and livelihoods. It shows how some countries are acting to reverse the crisis, protect those most vulnerable, and promote a resilient recovery. These findings call for urgent action. If the global response fails the world's poorest and most vulnerable people now, the losses they have experienced to date will be minimal compared with what lies ahead. Success over the long term will require much more than stopping COVID-19. As efforts to curb the disease and its economic fallout intensify, the interrupted development agenda in low- and middle-income countries must be put back on track. Recovering from today's reversals of fortune requires tackling the economic crisis unleashed by COVID-19 with a commitment proportional to the crisis itself. In doing so, countries can also plant the seeds for dealing with the long-term development challenges of promoting inclusive growth, capital accumulation, and risk prevention—particularly the risks of conflict and climate change.
Digital technologies are spreading rapidly, but digital dividends--the broader benefits of faster growth, more jobs, and better services--are not. If more than 40 percent of adults in East Africa pay their utility bills using a mobile phone, why can’t others around the world do the same? If 8 million entrepreneurs in China--one third of them women--can use an e-commerce platform to export goods to 120 countries, why can’t entrepreneurs elsewhere achieve the same global reach? And if India can provide unique digital identification to 1 billion people in five years, and thereby reduce corruption by billions of dollars, why can’t other countries replicate its success? Indeed, what’s holding back countries from realizing the profound and transformational effects that digital technologies are supposed to deliver? Two main reasons. First, nearly 60 percent of the world’s population are still offline and can’t participate in the digital economy in any meaningful way. Second, and more important, the benefits of digital technologies can be offset by growing risks. Startups can disrupt incumbents, but not when vested interests and regulatory uncertainty obstruct competition and the entry of new firms. Employment opportunities may be greater, but not when the labor market is polarized. The internet can be a platform for universal empowerment, but not when it becomes a tool for state control and elite capture. The World Development Report 2016 shows that while the digital revolution has forged ahead, its 'analog complements'--the regulations that promote entry and competition, the skills that enable workers to access and then leverage the new economy, and the institutions that are accountable to citizens--have not kept pace. And when these analog complements to digital investments are absent, the development impact can be disappointing. What, then, should countries do? They should formulate digital development strategies that are much broader than current information and communication technology (ICT) strategies. They should create a policy and institutional environment for technology that fosters the greatest benefits. In short, they need to build a strong analog foundation to deliver digital dividends to everyone, everywhere.
This study documents a semi-structural model developed for Sri Lanka. This model, extended with a fiscal sector block, is expected to serve as a core forecasting model in the process of the Central Bank of Sri Lanka’s move towards flexible inflation targeting. The model includes a forward-looking endogenous interest rate and foreign exchange rate policy rules allowing for flexible change in policy behavior. It is a gap model that allows for simultaneous identification of business cycle position and long-term equilibrium. The model was first calibrated and then its data-fit was improved using Bayesian estimation technique with relatively tight priors.
This report presents a comprehensive overview of recent and longer-term trends in productivity levels and growth in OECD countries, accession countries, key partners and some G20 countries.
This paper takes stock of forecasting and policy analysis system capacity development (FPAS CD), drawing extensively on the experience and lessons learned from developing FPAS capacity in the central banks. By sharing the insights gained during FPAS CD delivery and outlining the typical tools developed in the process, the paper aims to facilitate the understanding of FPAS CD within the IMF and to inform future CD on building macroeconomic frameworks. As such, the paper offers a qualitative assessment of the experience with FPAS CD delivery and the use of FPAS in the decision-making process in central banks.