Journal of International Economics Impact Factor 2024-2025 - ResearchHelpDesk - The Journal of International Economics is intended to serve as the primary outlet for theoretical and empirical research in all areas of international economics. These include, but are not limited to the following: trade patterns, commercial policy; international institutions; exchange rates; open economy macroeconomics; international finance; international factor mobility. The Journal especially encourages the submission of articles which are empirical in nature, or deal with issues of open economy macroeconomics and international finance. Theoretical work submitted to the Journal should be original in its motivation or modelling structure. Empirical analysis should be based on a theoretical framework, and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors. Abstracting and Indexing Current Contents Journal of Economic Literature Social Sciences Citation Index ABI/Inform UMI Data Courier RePEc

Asia Pacific Journal of Risk and Insurance Impact Factor 2024-2025 - ResearchHelpDesk - As the official journal of the Asia-Pacific Risk and Insurance Association, the Asia-Pacific Journal of Risk and Insurance (APJRI) focuses on risk management and insurance issues of importance to the Asia-Pacific region. An interdisciplinary publication, APJRI facilitates the exchange of research in risk and insurance mathematics, economics, finance, and corporate practice. The journal welcomes theoretical and applied research papers on a variety of specific topics. Topics Actuarial pricing and reserving Insurance operations Economics and regulation Corporate/enterprise risk management and finance Catastrophe risk Social insurance and employee benefits Local/regional/international insurance markets Abstracting & Indexing Asia-Pacific Journal of Risk and Insurance is covered by the following services: Baidu Scholar Bibliography of Asian Studies Cabell's Whitelist CNKI Scholar (China National Knowledge Infrastructure) CNPIEC - cnpLINKer Dimensions EBSCO (relevant databases) EBSCO Discovery Service EconBiz EconLit ERIH PLUS (European Reference Index for the Humanities and Social Sciences) Genamics JournalSeek Google Scholar Index Islamicus J-Gate JournalGuide JournalTOCs KESLI-NDSL (Korean National Discovery for Science Leaders) Microsoft Academic MyScienceWork Naver Academic Naviga (Softweco) Norwegian Register for Scientific Journals, Series and Publishers Primo Central (ExLibris) ProQuest (relevant databases) Publons QOAM (Quality Open Access Market) ReadCube Research Papers in Economics (RePEc) Semantic Scholar Sherpa/RoMEO Summon (ProQuest) TDNet Ulrich's Periodicals Directory/ulrichsweb WanFang Data WorldCat (OCLC)

Applied finance and accounting Impact Factor 2024-2025 - ResearchHelpDesk - Applied Finance and Accounting (ISSN 2374-2410; E-ISSN 2374-2429) is a peer-reviewed, open-access journal, published by Redfame Publishing. The journal is published semiannually (February, August) in both print and online versions. The journal accepts article submissions online or by e-mail. It publishes original research, applied, and educational articles in the areas of finance, accounting, and related disciplines. Authors are encouraged to submit complete unpublished and original works, which are not under review in any other journals. AFA is striving to provide the best platform for teachers and researchers worldwide to exchange their latest findings. Applied Finance and Accounting The scopes of the journal include, but not limited to, the following topic areas: Accounting/Auditing Asset Pricing Banking and Market Behavioural Finance Controlling Corporate Finance Experimental Finance Finance/Investment Fiscality Financial Accounting International Accounting Law and Finance Management Accounting Managerial Accounting Monetary Policy Tax Accounting Public Finance Public Administration Personal Finance The journal is included in: BASE (Bielefeld Academic Search Engine) CNKI Scholar Crossref EconPapers Google Scholar Citations IDEAS IE Library JournalTOCs LOCKSS PKP Open Archives Harvester Publons RePEc ROAD SocioRePEc The Standard Periodical Directory Worldcat

Abstract

To educate consumers about responsible use of financial products, many governments, non-profit organizations and financial institutions have started to provide financial literacy courses. However, participation rates for non-compulsory financial education programs are typically extremely low.

Researchers from the World Bank conducted randomized experiments around a large-scale financial literacy course in Mexico City to understand the reasons for low take-up among a general population, and to measure the impact of this financial education course. The free, 4-hour financial literacy course was offered by a major financial institution and covered savings, retirement, and credit use. Motivated by different theoretical and logistics reasons why individuals may not attend training, researchers randomized the treatment group into different subgroups, which received incentives designed to provide evidence on some key barriers to take-up. These incentives included monetary payments for attendance equivalent to $36 or $72 USD, a one-month deferred payment of $36 USD, free cost transportation to the training location, and a video CD with positive testimonials about the training.

A follow-up survey conducted on clients of financial institutions six months after the course was used to measure the impacts of the training on financial knowledge, behaviors and outcomes, all relating to topics covered in the course.

The baseline dataset documented here is administrative data received from a screener that was used to get people to enroll in the financial course. The follow-up dataset contains data from the follow-up questionnaire.

Geographic coverage

Mexico City

Analysis unit

-Individuals

Universe

Participants in a financial education evaluation

Kind of data

Sample survey data [ssd]

Sampling procedure

Researchers used three different approaches to obtain a sample for the experiment.

The first one was to send 40,000 invitation letters from a collaborating financial institution asking about interest in participating. However, only 42 clients (0.1 percent) expressed interest.

The second approach was to advertise through Facebook, with an ad displayed 16 million times to individuals residing in Mexico City, receiving 119 responses.

The third approach was to conduct screener surveys on streets in Mexico City and outside branches of the partner institution. Together this yielded a total sample of 3,503 people. Researchers divided this sample into a control group of 1,752 individuals, and a treatment group of 1,751 individuals, using stratified randomization. A key variable used in stratification was whether or not individuals were financial institution clients. The analysis of treatment impacts is based on the sample of 2,178 individuals who were financial institution clients.

The treatment group received an invitation to participate in the financial education course and the control group did not receive this invitation. Those who were selected for treatment were given a reminder call the day before their training session, which was at a day and time of their choosing.

Mode of data collection

Face-to-face [f2f]

Research instrument

The follow-up survey was conducted between February and July 2012 to measure post-training financial knowledge, behavior and outcomes. The questionnaire was relatively short (about 15 minutes) to encourage participation.

Interviewers first attempted to conduct the follow-up survey over the phone. If the person did not respond to the survey during the first attempt, researchers offered one a 500 pesos (US$36) Walmart gift card for completing the survey during the second attempt. If the person was still unavailable for the phone interview, a surveyor visited his/her house to conduct a face-to-face interview. If the participant was not at home, the surveyor delivered a letter with information about the study and instructions for how to participate in the survey and to receive the Walmart gift card. Surveyors made two more attempts (three attempts in total) to conduct a face-to-face interview if a respondent was not at home.

Response rate

72.8 percent of the sample was interviewed in the follow-up survey. The attrition rate was slightly higher in the treatment group (29 percent) than in the control group (25.3 percent).

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Which of the four factors directly impact your total cost of using the credit card?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Mini-Grid Social Impact Bond Market Outlook

According to our latest research, the global Mini-Grid Social Impact Bond market size reached USD 1.12 billion in 2024, reflecting robust momentum across emerging and developed economies. The market is projected to expand at a CAGR of 18.7% from 2025 to 2033, with the total market value forecasted to reach USD 5.98 billion by 2033. This remarkable growth is primarily driven by the increasing demand for sustainable infrastructure financing, a global push for rural electrification, and the rising prominence of impact investing as a mainstream financial strategy. As per our latest research, the convergence of social objectives and innovative financing mechanisms underpins the rapid evolution of the Mini-Grid Social Impact Bond market.

A primary growth factor in the Mini-Grid Social Impact Bond market is the urgent need for rural electrification in underserved regions, particularly in Sub-Saharan Africa, South Asia, and parts of Latin America. Traditional grid expansion has proven economically unviable and logistically challenging in remote communities, opening the door for decentralized mini-grid solutions. Social Impact Bonds (SIBs) and Development Impact Bonds (DIBs) offer a pragmatic approach by attracting private capital to fund these projects, with returns linked to measurable social outcomes such as increased access to electricity and improved community well-being. Moreover, the integration of renewable energy sources like solar and wind in mini-grid projects further strengthens their appeal among impact investors seeking both financial returns and positive environmental externalities. This alignment between social, environmental, and financial objectives is a key driver behind the growing adoption of Mini-Grid Social Impact Bonds.

Another significant catalyst for market expansion is the increasing participation of institutional investors, government agencies, and international development organizations in the impact investing ecosystem. Governments are increasingly leveraging public-private partnerships to de-risk investments in mini-grid infrastructure, while multilateral agencies such as the World Bank and regional development banks provide technical assistance and guarantee mechanisms. The proliferation of ESG (Environmental, Social, and Governance) investment mandates among pension funds and sovereign wealth funds has further accelerated capital inflows into social impact bonds. Additionally, the emergence of standardized measurement frameworks for social outcomes and improved transparency in impact reporting have enhanced investor confidence, stimulating further market growth. The growing sophistication of financial instruments tailored to social impact, including green and blended finance bonds, is also reshaping the competitive landscape.

Technological advancements and policy innovations are playing a pivotal role in shaping the Mini-Grid Social Impact Bond market. The adoption of digital platforms for project monitoring, impact measurement, and performance-based payments has streamlined the implementation and scalability of SIBs and DIBs. Governments and regulators are introducing favorable policies, such as feed-in tariffs, subsidies, and tax incentives, to incentivize private sector participation in mini-grid projects. The convergence of fintech solutions with social finance is enabling real-time data collection and transparent disbursement of funds, thereby reducing transaction costs and enhancing accountability. These developments are fostering trust among stakeholders and paving the way for the replication of successful models across diverse geographies.

From a regional perspective, Asia Pacific and Sub-Saharan Africa are emerging as the most dynamic markets for Mini-Grid Social Impact Bonds, driven by large populations without reliable electricity access and strong government support for decentralized energy solutions. North America and Europe, while more mature in terms of grid infrastructure, are witnessing growing interest in community-driven renewable energy projects and green bonds. Latin America and the Middle East & Africa are also experiencing increased activity, supported by international development finance and innovative public-private partnerships. The regional diversification of impact bond projects reflects the adaptability of the model to address varying socio-economic challenges and regulatory environments.

This data were collected from a randomised sample of 964 Australian general practitioners, with the aim of examining the impact a small financial incentive has on response rate and speed of the sample to a cross-sectional postal survey. Attached data includes; condition, ARIA status, survey sent date, survey return date. The response rate was calculated from the survey sent and return dates. ARIA status measures the remoteness of responders using a calculation of road networks. This research was supported by the National Health and Medical Research Council via a Dementia Research Team grant (APP1095078). Mariko Carey is supported by a NHMRC Boosting Dementia Research Leadership Fellowship (APP1136168). This research was also supported by infrastructure funding from the Hunter Medical Research Institute. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

According to Cognitive Market Research, the global Personal Finance Management Tools Market size will be USD XX million in 2024 and will expand at a compound annual growth rate (CAGR) of XX% from 2024 to 2033. Market Dynamics Key Driver

Key Drivers for Personal finance management tools market

Increasing investments in the market: The key Driver of Personal Finance Management Tools 

Increasing investment in the market Is driving the growth of financial tools, enhancing accessibility and efficiency in financial planning. The increasing investment in the market especially after Covid-19 had a significant impact on the expansion of the PFM tools market. The pandemic had a positive impact on the increase in savings and investments in the market due to future uncertainties. For instance, the study conducted on U.S. investors who have personal experience with COVID-19, who are in a vulnerable health category, who tested positive, and who know someone in their close circle of friends or family who died because of COVID-19, increase their investments by 12%. The increase in investment in the market is leading to the rise in the demand for personal finance management tools. For instance, as of 2023 about 3% of the Indian population actively invest in the stock market. This number has gradually grown, prominent reason for growth is access to technology and, more people becoming financially aware. According to NSE, more than 120 million investors were registered between 2019 and 2023 indicating a significant rise in Indian Stock Market. In January 2024 alone over 5.4 million new investors joined.

Rising financial literacy fuels the Financial Management tools market 

Financial literacy empowers individuals to make informed financial choices. The financial literacy rate among its young and adult population has been growing due to various factors including the recent advancement in technology and media coverage. Additionally, the policies formed by the government globally are leading to improved literacy rates. • For instance, the expansion of digital financial services has helped decrease the number of adults without access to an account from 2.5 billion in 2011 to 1.4 billion in 2021, with 76% of the global adult population owning an account by 2021. Countries achieving significant progress have implemented large-scale policies, such as India's Aadhaar initiative, which has provided over 1.2 billion residents with universal digital identification, facilitating the opening of Jan Dhan Yojana (JDY) accounts. Leveraging government payments has also been instrumental; for instance, 35% of adults in low-income countries who received government payments opened their first financial account for this purpose.
• For instance, according to survey each person in China, on average, had 10 accounts and 7 cards at the end of 2023. The steps taken by the government had a significant impact on financial literacy leading to financial inclusion which has made people aware about the investment choices available in the market leading to the expansion in the PFM tools market.

Restraints

Security and compliance risks pose challenges for AI-powered financial tools, making data protection crucial to prevent cyber threats and frauds.

AI-powered financial tools can pose privacy and security risks. Personal financial information is sensitive data that can be vulnerable to cyberattacks and data breaches. It's important to use financial tools that have robust security features in place to protect your information and minimize the risk of unauthorized access. The most common scams in PFM tools include phishing, insider trading, money laundering and mortgage fraud. Phishing attacks are a significant threat to the financial sector, with attackers often targeting financial institutions and individuals to steal credentials or financial information. For instance, in 2024, India saw a 175% surge in phishing attacks targeting the financial sector, with over 135,000 incidents reported from January to June. According to SlashNext’s 2024 Phishing Intelligence Report, a substantial 703% surge in credential phishing attacks was also observed in the same period. AI in financial tools presents compliance challenges related to data privacy, security, algorithmic bias, transparency, and accountability, requir...

This dataset contains the monthly historical data of the S&P 500 index from January 1901 to May 2025, collected from Investing.com. The S&P 500 is a stock market index that tracks the performance of 500 large companies listed on stock exchanges in the United States.

It is widely used as a benchmark for the U.S. equity market, representing over 80% of the total market capitalization. This dataset is suitable for:

• Time-series forecasting
• Economic event impact analysis (e.g., wars, recessions, pandemics)
• Financial visualizations in Tableau or Power BI
• Quantitative finance and portfolio management research

Column Descriptions

Potential Use Cases:

• Visualizing market impact of wars, financial crises, and pandemics
• Analyzing long-term trends in the U.S. equity market
• Forecasting future index levels using machine learning
• Annotating economic history alongside market movements

Citation:

Data source: Investing.com

Blue Economy Impact Fund Market Outlook

According to our latest research, the Blue Economy Impact Fund market size reached USD 12.7 billion globally in 2024, demonstrating robust momentum driven by growing environmental awareness and sustainable investment trends. The market is expected to maintain a strong trajectory, registering a CAGR of 13.2% from 2025 to 2033. By 2033, the Blue Economy Impact Fund market is forecasted to reach USD 38.3 billion. This growth is primarily fueled by increasing capital inflows into sustainable ocean-related projects, rising regulatory support for blue economy initiatives, and heightened demand for responsible investment vehicles that address marine conservation and climate resilience.

A key growth factor for the Blue Economy Impact Fund market is the global shift toward sustainable finance, with investors and governments recognizing the critical role of oceans in climate regulation, food security, and economic development. The escalating threats of overfishing, marine pollution, and habitat loss have prompted a surge in impact funds specifically targeting ocean health, sustainable fisheries, and coastal ecosystem restoration. Institutional investors are increasingly allocating capital to blue economy projects, attracted by both the long-term financial returns and measurable environmental and social impact. As a result, innovative financial instruments and blended finance models are proliferating, enabling greater participation from private, public, and philanthropic sectors in blue economy initiatives.

Another significant driver is the technological advancement and commercialization of marine solutions, such as renewable ocean energy, marine biotechnology, and advanced waste management systems. These innovations are opening new avenues for investment and scaling up the impact of blue economy funds. The emergence of digital monitoring tools, satellite-based ocean analytics, and sustainable aquaculture technologies is enhancing transparency, risk management, and performance measurement for investors. Furthermore, the growing adoption of ESG (Environmental, Social, and Governance) criteria in investment decisions is reinforcing the appeal of blue economy funds, as stakeholders increasingly demand robust impact verification and alignment with global sustainability frameworks like the UN Sustainable Development Goals (SDGs).

The policy landscape is also evolving favorably for the Blue Economy Impact Fund market. Governments worldwide are implementing policy incentives, regulatory frameworks, and public-private partnerships to catalyze investments in ocean-based sectors. Blue bonds, sovereign funds, and national blue economy strategies are being deployed to mobilize capital at scale and de-risk investments in sustainable marine projects. Multilateral organizations and development banks are actively supporting capacity building, technical assistance, and risk-sharing mechanisms, which further enhance the attractiveness and viability of blue economy impact funds. These policy developments are expected to underpin sustained market growth and foster innovation across the investment value chain.

Regionally, Europe remains a frontrunner in the Blue Economy Impact Fund market, accounting for the largest share in 2024, driven by strong regulatory support, well-established financial markets, and a mature ecosystem of sustainable investors. North America is rapidly catching up, propelled by increasing investor awareness, rising ESG mandates, and significant technological advancements in marine industries. The Asia Pacific region is witnessing accelerated growth due to expanding coastal economies, government initiatives, and a burgeoning middle class demanding sustainable seafood and eco-tourism. Meanwhile, Latin America and the Middle East & Africa are emerging as promising markets, leveraging their vast marine resources and international development cooperation to attract blue economy investments. This regional diversity is expected to shape the competitive dynamics and innovation landscape of the global Blue Economy Impact Fund market in the coming years.

Fund Type Analysis

The Fund Type segment within the Blue Economy Impact Fund market is pivotal in shaping capital allocation strategies and risk-return profiles for investors. Equity funds represent a significant portion of the market, channeling investments into high-growth marine startups, su

Indian Journal of Finance and Banking Impact Factor 2024-2025 - ResearchHelpDesk - Indian Journal of Finance and Banking (IJFB) is an international, double-blind peer-reviewed, scholarly open access journal on the financial market, instruments, policy, and management research published both online and print by CRIBFB. Aims & Scope The subject areas include, but are not limited to the following fields: Insurance Uncertainty Portfolio Theory Asset Pricing Futures Markets Investment Policy Agency Theory Risk Management Banking Systems Computational Finance Behavioral Finance Financial Econometrics Corporate Governance Credit and Market Risk Advanced Stochastic Methods Financial Intermediation Public Finance Management Financial Regulation and Policy Fiscal Markets and Instruments Financial Derivatives Research Financial Instruments for Risk Management Statistical and Empirical Financial Studies Asset-Liability Management Bank Assurance Banking Crises Derivatives and Structured Financial Products Efficiency and Performance of Financial Institutions and Bank Branches Financing Decisions of Banks Investment Banking Management of Financial Institutions Technological Progress and Banking Foreign Exchange Management Conventional Vs. Non-Conventional Banking Internet Banking Mobile Banking Retail Banking E-Banking CSR of Bank SMEs Banking Bankruptcy Prediction and Determinants Corporate Finance International Finance Rural Finance Fixed Income Securities Alternative Investments Portfolio and Security Analysis Time Value of Money Credit Risk Modelling and Management Financial Engineering Foreign Exchange Markets Law and Finance Mergers and Acquisitions Mutual Funds Management Portfolio Management Regulations of Financial Markets Venture Capital Microcredit Valuation Risk and Return Liquidity Management Foreign Direct Investment Financial Accounting Financial Statement Analysis Microeconomics Econometrics models Macroeconomics Information in Relation to Finance, Banking, and Business, etc. Indian Journal of Finance and Banking currently has an acceptance rate of 25%. The average time between submission and final decision is 20 days and the average time between acceptance and publication is 30 days.

Snapshot img

The fintech investment market share is expected to increase by USD 54.56 billion from 2020 to 2025, and the market’s growth momentum will accelerate at a CAGR of 7.76%.

This fintech investment market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers fintech investment market segmentations by investment area (digital payments, insurance, and others) and geography (APAC, North America, Europe, South America, and MEA). The fintech investment market report also offers information on several market vendors, including Ant Technology Group Co. Ltd., Avant LLC, Berkshire Hathaway Inc., Facebook Inc., Funding Circle Holdings Plc, KPMG International Ltd., Oscar Insurance Corp., SoftBank Group Corp., Wealthfront Corp., and ZhongAn Online Property Insurance Co. Ltd. among others.

What will the FinTech Investment Market Size be During the Forecast Period?

Download the Free Report Sample to Unlock the FinTech Investment Market Size for the Forecast Period and Other Important Statistics

FinTech Investment Market: Key Drivers, Trends, and Challenges

Based on our research output, there has been a negative impact on the market growth during and post COVID-19 era. The disintermediation of banking services is notably driving the fintech investment market growth, although factors such as privacy and security concerns may impede market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the fintech investment industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

Key FinTech Investment Market Driver

One of the key factors driving the fintech investment market growth is disintermediation of banking services. It is estimated that the top banking institutions may develop a strategic approach, such as the development of smartphone payment technologies, to deal with competition from fintech platforms during the forecast period. Equity investment searches have entered the online domain where a huge number of venture capitalists are investing in the market. Angel List is operating as a main business angel network, while other providers are helping to clear investment payments (known as equity crowdfunding). Bitcoin is a virtual currency and a payment system that hinges on software and online transactions. It represents an innovative and secure cryptocurrency that can be bought with traditional money. Transactions that take place in bitcoin currency operate through peer-to-peer technology. Companies such as Microsoft are investing in virtual currencies, whereas other firms like Apple and Google are concentrating on wallets that allow online transactions. Such factors of adoption of blockchain technologies and digital wallets are expected to drive the market in focus during the forecast period.

Key FinTech Investment Market Trend

Innovation and development is the major trend influencing the fintech investment market growth. Fintech startups in New York, Silicon Valley, London, and Australia are registering steady business progress. Their customers are opting for tech-enabled payments, currency exchanges, crowdfunding, online lending, and wealth-management services. This is helping fintech startup firms to gain the upper hand over traditional banking systems and other firms in the financial system. In 2011, the fintech industry did not attract much investment, as in the wake of the 2008 global economic crisis, financial institutions focused on cost-cutting measures to maintain profit margins. There was less attention on investments or embracing new and innovative technologies. However, the current market scenario presents a better picture, with the industry launching new technological products. Major banks are helping to incubate, invest in, or partner with fintech companies. This trend indicates that financial institutions are embracing digital innovations in a bid to strengthen their brand values.

Key FinTech Investment Market Challenge

Privacy and security concerns is one of the key challenges hindering the fintech investment market growth. Payment service providers gather personal data and information about customers so that they can customize advertising messages and target key audiences. Such practices help service providers collect data on customer profiling, behavior, and data mining. However, the indiscriminate use of this data can infringe on customer privacy. Location-based services also have privacy concerns because such offerings and services operate on the basis of real-time, geo-based information. The data collected from smartphone devices is processed and stored by vendors and so remains open to abuse. As smartphones are used in monetary trans

Abstract

This research was conducted in Vietnam between June 2009 and January 2010 as part of the Enterprise Survey initiative.

The objective of the survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Vietnam was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into 6 manufacturing industries, 1 services industry -retail -, and two residual sectors. Each manufacturing industry had a target of 160 interviews. The services industry and the two residual sectors had a target of 120 interviews. For the manufacturing industries sample sizes were inflated by about 33% to account for potential non-response cases when requesting sensitive financial data and also because of likely attrition in future surveys that would affect the construction of a panel. An additional 85 interviews were added to the survey half way through the fieldwork. Targets were adjusted such that the manufacturing sectors' targets were increased to 160-180 interviews.

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification was defined in five regions containing 14 provinces: Red River Delta (Hanoi, Ha Tay, Hai Duong, and Hai Phong), the North Centre Coast (Thanh Hoa, Nghe An), Mekong River Delta (Can Tho, Long An, Tien Giang), South Centre Coast (Khanh Hoa, Da Nang) and South East (Ho Chi Minh City, Binh Duong, Dong Nai).

Two frames were used for Vietnam. The sample frame containing fresh contacts used in the Vietnam was obtained from the 2008 Vietnam General Statistics Office. A frame containing firms that had participated in the 2005 survey constituted a second frame of panel contacts. Each database contained the following information: -Name of the firm -Location -Contact details -ISIC code -Number of employees.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 23% (734 out of 3131 establishments). Breaking down by industry, the following numbers of establishments were surveyed: 15 (Food) - 127, 17 (Textiles) -120, 18 (Garments) - 120, 26 (Non-metallic mineral products) - 123, 28 (Metal & Fabrication) - 122, Other manufacturing - 196, Retail & IT - 128, Other services - 117.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Screener Questionnaire.

The “Core Questionnaire” is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments- the “Core Questionnaire + Manufacturing Module” and the “Core Questionnaire + Retail Module.” The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Vietnam Implementation 2009" in "Technical Documents" folder.