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Asia and Pacific > India

You are looking at 1 - 10 of 63 items for :

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Cover IMF Working Papers
Unveiling the Informal Economy: An Augmented Factor Model Approach
Jiaxiong Yao
This paper develops a new approach to estimating the degree of informality in an economy. It combines direct yet infrequent measures of the informal economy in micro data with an augmented factor model that links macro indicators of the informal economy to its causes. We show that the prevailing model used in the literature, the multiple indicators multiple causes model, is a special case of the augmented factor model and depicts an incomplete picture of the informal economy. Using the augmented factor model approach, we show that the dynamics of the informal economy is shaped by the strength of overall economic activity as well as the interplay between the formal and informal economies. Contrary to previous work that typically finds declining informality for most countries, we find that the degree of informality has increased for low-income countries for the past two decades.
Keywords:
Informality; augmented factor model; MIMIC model; survey data; indicators of the informal economy; WBES data; D. adding nighttime; nighttime Light; component analysis; Informal economy; Factor models; Monetary base; Electricity; Consumption; Global
Cover IMF Staff Country Reports
India: 2023 Article IV Consultation-Press Release; Staff Report; and Statement by the Executive Director for India
International Monetary Fund. Asia and Pacific Dept
The 2023 Article IV Consultation highlights that India is on track to be one of the fastest growing major economies in the world this year, underpinned by prudent macroeconomic policies. Nonetheless, the economy is facing global headwinds, including a global growth slowdown in an increasingly fragmented world. Policy priorities should focus on replenishing fiscal buffers, securing price stability, maintaining financial stability, and accelerating inclusive growth through comprehensive structural reforms while preserving debt sustainability. Elevated public debt calls for ambitious medium-term consolidation, while continuing to prioritize capital spending. This should be complemented with a sound medium-term fiscal framework to promote transparency and accountability and align policies with India’s development goals. In order to reap the benefits of demographic tailwinds, structural policy should focus on promoting high quality job-rich growth, underpinned by comprehensive reform in areas of education, health, land, agriculture, and labor markets, including measures to boost female labor force participation. Continuing investment in infrastructure, strengthening governance, and enhancing a sound business environment are critical.
Keywords:
policy priority; WPI base year; infrastructure program; CPI series; household inflation expectation; gross investment; policy recommendation; financial asset; FDI regime; fund approval; CPI weight; Inflation; Government debt management; Global
Cover IMF Working Papers
Predicting the Law: Artificial Intelligence Findings from the IMF’s Central Bank Legislation Database
Khaled AlAjmi
,
Jose Deodoro
,
Mr. Ashraf Khan
, and
Kei Moriya
Using the 2010, 2015, and 2020/2021 datasets of the IMF’s Central Bank Legislation Database (CBLD), we explore artificial intelligence (AI) and machine learning (ML) approaches to analyzing patterns in central bank legislation. Our findings highlight that: (i) a simple Naïve Bayes algorithm can link CBLD search categories with a significant and increasing level of accuracy to specific articles and phrases in articles in laws (i.e., predict search classification); (ii) specific patterns or themes emerge across central bank legislation (most notably, on central bank governance, central bank policy and operations, and central bank stakeholders and transparency); and (iii) other AI/ML approaches yield interesting results, meriting further research.
Keywords:
central bank legislation; central banking; artificial intelligence; machine learning; Bayesian algorithm; Boolean algorithm; central bank governance; law and economics; ML approach; IMF central bank transparency code; IMF Central Bank Legislation Database; capital markets Department; approaches to analyzing pattern; CBLD data flow; Central bank autonomy; Central bank transparency; Global
Cover IMF Working Papers
Global Economic Impacts of Physical Climate Risks
Caterina Lepore
and
Roshen Fernando
This paper evaluates the global economic consequences of physical climate risks under two Shared Socioeconomic Pathways (SSP 1-2.6 and SSP 2-4.5) using firm-level evidence. Firstly, we estimate the historical sectoral productivity changes from chronic climate risks (gradual changes in temperature and precipitation) and extreme climate conditions (representative of heatwaves, coldwaves, droughts, and floods). Secondly, we produce forward-looking sectoral productivity changes for a global multisectoral sample of firms. For floods, these estimates account for the persistent productivity changes from the damage to firms’ physical capital. Thirdly, we assess the macroeconomic impact of these shocks within the global, multisectoral, intertemporal general equilibrium model: G-Cubed. The results indicate that, in the absence of additional adaptation relative to that already achieved by 2020, all the economies would experience substantial losses under the two climate scenarios and the losses would increase with global warming. The results can be useful for policymakers and practitioners interested in conducting climate risk analysis.
Keywords:
climate risk analysis; capital markets department; climate risk; physical capital; productivity change; Climate change; Productivity; Agricultural sector; Natural disasters; Global; North America; Western Europe; Europe
Cover IMF Working Papers
Identifying Optimal Indicators and Lag Terms for Nowcasting Models
Jing Xie
Many central banks and government agencies use nowcasting techniques to obtain policy relevant information about the business cycle. Existing nowcasting methods, however, have two critical shortcomings for this purpose. First, in contrast to machine-learning models, they do not provide much if any guidance on selecting the best explantory variables (both high- and low-frequency indicators) from the (typically) larger set of variables available to the nowcaster. Second, in addition to the selection of explanatory variables, the order of the autoregression and moving average terms to use in the baseline nowcasting regression is often set arbitrarily. This paper proposes a simple procedure that simultaneously selects the optimal indicators and ARIMA(p,q) terms for the baseline nowcasting regression. The proposed AS-ARIMAX (Adjusted Stepwise Autoregressive Moving Average methods with exogenous variables) approach significantly reduces out-of-sample root mean square error for nowcasts of real GDP of six countries, including India, Argentina, Australia, South Africa, the United Kingdom, and the United States.
Keywords:
Nowcasting; Mixed Frequency; Forecasting; Business Cycles; selection procedure; Annex I. AS-ARIMAX procedure; nowcasting method; evaluation comparison; baseline model; Global
Cover IMF Working Papers
Financial Sector and Economic Growth in India
Ms. Margaux MacDonald
and
Ms. TengTeng Xu
India’s financial sector has faced many challenges in recent decades, with a large, negative, and persistent credit to GDP gap since 2012. We examine how cyclical financial conditions affect GDP growth using a growth-at-risk (GaR) approach and analyze the link between bank balance sheets, credit growth, and long-term growth using bank-level panel regressions for both public and private banks. We find that on a cyclical basis, a negative shock to credit or a rise in macro vulnerability all shift the distribution of growth to the left, with lower expected growth and higher negative tail risks; over the long term, the results indicate that higher credit growth, arising from better capitalized banks with lower NPLs, is associated with higher GDP growth.
Keywords:
India; Credit and Leverage; Macro-financial Linkages; Growth-at-Risk; Panel Regressions.; credit growth; cyclical financial conditions; economic growth in India; GDP gap; bank capitalization; Credit; Bank credit; State-owned banks; Debt financing; Financial statements; Global; NPL ratio; bank equity; bank assets; growth from bank
Cover IMF Staff Country Reports
Bhutan: 2022 Article IV Consultation-Press Release; Staff Report; and Statement by the Executive Director for Bhutan
International Monetary Fund. Asia and Pacific Dept
The pandemic has had a substantial impact on the economy, straining pre-pandemic gains in income and poverty reduction. The wide-ranging policy measures, including containment protocols, rapid vaccination and booster campaigns, direct income support, and policy support for borrowers and businesses, mitigated the adverse impact on lives and well-being. As the pandemic recedes and in light of the uncertainties from the war in Ukraine, the focus needs to be on securing livelihoods and ensuring strong and job-rich medium-term growth, while minimizing any persistent adverse effects from the pandemic and mitigating risks.
Keywords:
development goal; quarterly balance of payments; income support; FDI investment rule; Five-Year Plans; food price; COVID-19; Debt sustainability; Debt sustainability analysis; Global; South Asia
Cover IMF Working Papers
Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa
Karim Barhoumi
,
Seung Mo Choi
,
Tara Iyer
,
Jiakun Li
,
Franck Ouattara
,
Mr. Andrew J Tiffin
, and
Jiaxiong Yao
The COVID-19 crisis has had a tremendous economic impact for all countries. Yet, assessing the full impact of the crisis has been frequently hampered by the delayed publication of official GDP statistics in several emerging market and developing economies. This paper outlines a machine-learning framework that helps track economic activity in real time for these economies. As illustrative examples, the framework is applied to selected sub-Saharan African economies. The framework is able to provide timely information on economic activity more swiftly than official statistics.
Keywords:
Sub-Saharan Africa; Economic Activity; GDP; Machine Learning; Nowcasting; COVID-19; machine learning approach; data sparsity; GDP statistics; crisis in Sub-Saharan Africa; learning framework; Oil prices; Real effective exchange rates; Africa; Global
Cover IMF Staff Country Reports
India: 2021 Article IV Consultation-Press Release; Staff Report; and Statement by the Executive Director for India
International Monetary Fund. Asia and Pacific Dept
The ongoing COVID-19 pandemic has created a prolonged health crisis. Economic activity was slowing prior to the pandemic. Two COVID-19 waves have resulted in a deep and broad-based economic downturn with the potential for a longer lasting impact. The authorities have responded with fiscal policy, including scaled-up support to vulnerable groups, monetary policy easing and liquidity provision, and accommodative financial sector and regulatory policies. Despite the pandemic, the authorities have continued to implement structural reforms.
Keywords:
headline consumer price inflation; The Authorities; potential GDP; labour market functioning; monetary policy easing; privatization of government enterprise; COVID-19; Government debt management; Global; Eastern Europe
Cover IMF Working Papers
Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050
Ms. Florence Jaumotte
,
Weifeng Liu
, and
Warwick J. McKibbin
Background paper prepared for the October 2020 IMF World Economic Outlook. This paper provides a detailed presentation of the simulation results from the October 2020 IMF World Economic Outlook chapter 3 and an additional scenario with carbon pricing only for comparison with the comprehensive policy package where green investments were also included. This paper has greatly benefitted from continuous discussions with Oya Celasun and Benjamin Carton on the design of simulations; contributions from Philip Barrett for part of the simulations; and research support from Jaden Kim. We also received helpful comments from other IMF staff. All remaining errors are ours. McKibbin and Liu acknowledge financial support from the Australian Research Council Centre of Excellence in Population Ageing Research (CE170100005).
Keywords:
policy package; climate mitigation strategy; baseline CO2 emission; scenario design; B. Policy tool; Carbon tax; Greenhouse gas emissions; Non-renewable resources; Climate finance; Global; Europe