This dataset provides a comprehensive collection of information about all the latest smartphones available in the market as of the current time.

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The dataset was created by web scraping reputable online sources to gather accurate and up-to-date information about various smartphone models, their specifications, features, and pricing.

Success.ai’s Phone Number Data offers direct access to over 50 million verified phone numbers for professionals worldwide, extracted from our expansive collection of 170 million profiles. This robust dataset includes work emails and key decision-maker profiles, making it an essential resource for companies aiming to enhance their communication strategies and outreach efficiency. Whether you're launching targeted marketing campaigns, setting up sales calls, or conducting market research, our phone number data ensures you're connected to the right professionals at the right time.

Why Choose Success.ai’s Phone Number Data?

Direct Communication: Reach out directly to professionals with verified phone numbers and work emails, ensuring your message gets to the right person without delay. Global Coverage: Our data spans across continents, providing phone numbers for professionals in North America, Europe, APAC, and emerging markets. Continuously Updated: We regularly refresh our dataset to maintain accuracy and relevance, reflecting changes like promotions, company moves, or industry shifts. Comprehensive Data Points:

Verified Phone Numbers: Direct lines and mobile numbers of professionals across various industries. Work Emails: Reliable email addresses to complement phone communications. Professional Profiles: Decision-makers’ profiles including job titles, company details, and industry information. Flexible Delivery and Integration: Success.ai offers this dataset in various formats suitable for seamless integration into your CRM or sales platform. Whether you prefer API access for real-time data retrieval or static files for periodic updates, we tailor the delivery to meet your operational needs.

Competitive Pricing with Best Price Guarantee: We provide this essential data at the most competitive prices in the industry, ensuring you receive the best value for your investment. Our best price guarantee means you can trust that you are getting the highest quality data at the lowest possible cost.

Targeted Applications for Phone Number Data:

Sales and Telemarketing: Enhance your telemarketing campaigns by reaching out directly to potential customers, bypassing gatekeepers. Market Research: Conduct surveys and research directly with industry professionals to gather insights that can shape your business strategy. Event Promotion: Invite prospects to webinars, conferences, and seminars directly through personal calls or SMS. Customer Support: Improve customer service by integrating accurate contact information into your support systems. Quality Assurance and Compliance:

Data Accuracy: Our data is verified for accuracy to ensure over 99% deliverability rates. Compliance: Fully compliant with GDPR and other international data protection regulations, allowing you to use the data with confidence globally. Customization and Support:

Tailored Data Solutions: Customize the data according to geographic, industry-specific, or job role filters to match your unique business needs. Dedicated Support: Our team is on hand to assist with data integration, usage, and any questions you may have. Start with Success.ai Today: Engage with Success.ai to leverage our Phone Number Data and connect with global professionals effectively. Schedule a consultation or request a sample through our dedicated client portal and begin transforming your outreach and communication strategies today.

Remember, with Success.ai, you don’t just buy data; you invest in a partnership that grows with your business needs, backed by our commitment to quality and affordability.

In 2021, the number of mobile devices operating worldwide stood at almost 15 billion, up from just over 14 billion in the previous year. The number of mobile devices is expected to reach 18.22 billion by 2025, an increase of 4.2 billion devices compared to 2020 levels.

Moving forward with 5G

As the number of devices grows, so does our dependence on them to fulfill daily functions and activities. The use cases for mobile devices increasingly demand faster connection speeds and lower latency. The 5G network will be critical to fulfilling those demands, operating at significantly faster rates than 4G. In North America, for example, it is expected that there will be 218 million 5G connections, up from just ten million in 2020. This means around 48 percent of all mobile connections in North America. Globally, this figure should reach 20.1 percent by 2025.

6G: looking beyond 5G

While 5G has entered commercialization and is already creating new opportunities, researchers and engineers are already experimenting with 6G. Not only will the number of mobile devices continue to grow but cellular internet-of-things (IoT) devices are set to permeate more industrial sectors in the coming years, meaning a solution will eventually be required for network congestion and data transfer speeds.

6G ought to be capable of solving those problems before they arise, potentially enabling a network connection density ten times greater than that of 5G, and peak data rates up to fifty times faster than the rate of 5G. The Federal Communications Commission in the United States has opened spectrum for experimentation, and China have already launched what is described as a 6G satellite, so that actual potential of 6G should be revealed over the coming decade.

Global B2B Mobile Phone Number Database | 100M+ Verified Contacts | 95% Accuracy Forager.ai provides the world’s most reliable mobile phone number data for businesses that refuse to compromise on quality. With 100 million+ professionally verified mobile numbers refreshed every 3 weeks, our database ensures 95% accuracy – so your teams never waste time on dead-end leads.

Why Our Data Wins ✅ Accuracy You Can Trust 95% of mobile numbers are verified against live carrier records and tied to current job roles. Say goodbye to “disconnected number” voicemails.

✅ Depth Beyond Digits Each contact includes 150+ data points:

Direct mobile numbers

Current job title, company, and department

Full career history + education background

Location data + LinkedIn profiles

Company size, industry, and revenue

✅ Freshness Guaranteed Bi-weekly updates combat job-hopping and role changes – critical for sales teams targeting decision-makers.

✅ Ethically Sourced & Compliant First-party collected data with full GDPR/CCPA compliance.

Who Uses This Data?

Sales Teams: Cold-call C-suite prospects with verified mobile numbers.

Marketers: Run hyper-personalized SMS/WhatsApp campaigns.

Recruiters: Source passive candidates with up-to-date contact intel.

Data Vendors: License premium datasets to enhance your product.

Tech Platforms: Power your SaaS tools via API with enterprise-grade B2B data.

Flexible Delivery, Instant Results

API (REST): Real-time integration for CRMs, dialers, or marketing stacks

CSV/JSON: Campaign-ready files.

PostgreSQL: Custom databases for large-scale enrichment

Compliance: Full audit trails + opt-out management

Why Forager.ai? → Proven ROI: Clients see 62% higher connect rates vs. industry averages (request case studies). → No Guesswork: Test-drive free samples before committing. → Scalable Pricing: Pay per record, license datasets, or get unlimited API access.

B2B Mobile Phone Data | Verified Contact Database | Sales Prospecting Lists | CRM Enrichment | Recruitment Phone Numbers | Marketing Automation | Phone Number Datasets | GDPR-Compliant Leads | Direct Dial Contacts | Decision-Maker Data

Need Proof? Contact us to see why Fortune 500 companies and startups alike trust Forager.ai for mission-critical outreach.

📱 Global Mobile Reviews Dataset (2025 Edition)

🌍 Research-Based, Web-Scraped Global Review Collection

This dataset presents a curated collection of over 50,000 mobile phone reviews gathered through web scraping, market analysis, and content aggregation from multiple e-commerce and tech review platforms.
It covers eight countries and includes detailed user opinions, ratings, sentiment polarity, and pricing data across leading smartphone brands.

Each record captures customer experience holistically — spanning demographics, verified purchase details, multi-aspect ratings, and currency-adjusted pricing — making this dataset a powerful asset for research, NLP, and analytics.

🎯 Ideal For

• 🧠 Sentiment Analysis & NLP Modeling
• 💬 Text Classification & Review Mining
• 💰 Market Research & Pricing Analytics
• 📊 Consumer Behavior Studies
• 🤖 AI Model Training & Data Science Projects

🧩 Key Highlights

• 50,000+ mobile reviews scraped from top global sources
• Reviews across 8 major countries and multiple platforms
• Demographic data (customer name, age, location)
• Verified purchase flags for reliability
• Detailed product-level sub-ratings
• Pricing in both USD and local currencies
• Multilingual data support and country-specific sentiment distribution
• Professionally cleaned and normalized for research applications

📦 Brands Covered

🌐 Countries Represented

🧾 Example Record

📈 Research & Analytical Applications

• Sentiment Mining: Detect sentiment polarity in real-world review text
• Cross-Country Analysis: Compare satisfaction trends by region and currency
• Price–Rating Studies: Explore pricing elasticity and value perception
• Demographic Insights: Link sentiment to user age and verified purchase behavior
• Market Comparison: Understand brand trust and perception across regions

🧪 Data Collection & Research Approach

This dataset was compiled through an extensive research process combining web scraping, content aggregation, and analytical validation from multiple open and public review sources including:

• E-commerce platforms (e.g., Amazon, Flipkart, BestBuy, eBay)
• Tech review forums and discussion threads
• Mobile product feedback portals and blogs

Data was then: - Filtered for quality and consistency
- Mapped with real-world pricing and currency exchange rates
- Manually validated for sentiment balance and linguistic variation

⚠️ Note: All data is collected from publicly available review information and anonymized for research and educational use only.
No private or personally identifiable data was used or retained.

🧩 Research Summary

The dataset provides a multi-dimensional representation of the modern mobile ecosystem — integrating global pricing, sentiment trends, and demographic diversity to aid data scientists, researchers, and AI practitioners in building better understanding of customer perspectives.

The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total *** billion users (+***** percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach *** billion users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like the Americas and Asia.

The average for 2023 based on 156 countries was 120.02 subscribers per 100 people. The highest value was in Hong Kong: 319.49 subscribers per 100 people and the lowest value was in Papua New Guinea: 34.06 subscribers per 100 people. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

Graph and download economic data for Mobile Cellular Subscriptions in the United States (ITCELSETSP2USA) from 1960 to 2023 about phone, telecom, and USA.

Abstract

To facilitate the use of data collected through the high-frequency phone surveys on COVID-19, the Living Standards Measurement Study (LSMS) team has created the harmonized datafiles using two household surveys: 1) the country’ latest face-to-face survey which has become the sample frame for the phone survey, and 2) the country’s high-frequency phone survey on COVID-19.

The LSMS team has extracted and harmonized variables from these surveys, based on the harmonized definitions and ensuring the same variable names. These variables include demography as well as housing, household consumption expenditure, food security, and agriculture. Inevitably, many of the original variables are collected using questions that are asked differently. The harmonized datafiles include the best available variables with harmonized definitions.

Two harmonized datafiles are prepared for each survey. The two datafiles are: 1. HH: This datafile contains household-level variables. The information include basic household characterizes, housing, water and sanitation, asset ownership, consumption expenditure, consumption quintile, food security, livestock ownership. It also contains information on agricultural activities such as crop cultivation, use of organic and inorganic fertilizer, hired labor, use of tractor and crop sales. 2. IND: This datafile contains individual-level variables. It includes basic characteristics of individuals such as age, sex, marital status, disability status, literacy, education and work.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

See “Ethiopia - Socioeconomic Survey 2018-2019” and “Ethiopia - COVID-19 High Frequency Phone Survey of Households 2020” available in the Microdata Library for details.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

Ethiopia Socioeconomic Survey (ESS) 2018-2019 and Ethiopia COVID-19 High Frequency Phone Survey of Households (HFPS) 2020 data were harmonized following the harmonization guidelines (see “Harmonized Datafiles and Variables for High-Frequency Phone Surveys on COVID-19” for more details).

The high-frequency phone survey on COVID-19 has multiple rounds of data collection. When variables are extracted from multiple rounds of the survey, the originating round of the survey is noted with “_rX” in the variable name, where X represents the number of the round. For example, a variable with “_r3” presents that the variable was extracted from Round 3 of the high-frequency phone survey. Round 0 refers to the country’s latest face-to-face survey which has become the sample frame for the high-frequency phone surveys on COVID-19. When the variables are without “_rX”, they were extracted from Round 0.

Response rate

See “Ethiopia - Socioeconomic Survey 2018-2019” and “Ethiopia - COVID-19 High Frequency Phone Survey of Households 2020” available in the Microdata Library for details.

In 2022, the average data used per smartphone per month worldwide amounted to ** gigabytes (GB). The source forecasts that this will increase almost four times reaching ** GB per smartphone per month globally in 2028.

The average for 2023 based on 156 countries was 54.59 million subscribers. The highest value was in China: 1824.42 million subscribers and the lowest value was in Palau: 0.02 million subscribers. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

Abstract

As of June 7, 2015, Sierra Leone had reported more than 12,900 cases of Ebola Virus Disease (EVD), and over 3,900 deaths since the outbreak began. The Government of Sierra Leone, with support from the World Bank Group, has been conducting mobile phone surveys with the aim of capturing the key socio-economic effects of the virus. Three rounds of data collection have been conducted, in November 2014, January-February 2015, and May 2015. The survey was given to household heads for whom cell phone numbers were recorded during the nationally representative Labor Force Survey conducted in July and August 2014. Overall, 66 percent of the 4,199 households sampled in that survey had cell phones, although this coverage was uneven across the country, with higher levels in urban areas (82 percent) than rural areas (43 percent). Of those with cell phones, 51 percent were surveyed in all three rounds, and 79 percent were reached in at least one round.

The main focus of the data collection was to capture impacts of EVD on labor market indicators, agricultural production, food security, migration, and utilization of non-Ebola essential health services.

Geographic coverage

Due to differing characteristics between responding and non-responding households, the results should be considered “descriptive” rather than representative of the Sierra Leonean population. Overall the response rate was higher than expected given the nature of the survey and the difficult conditions under which it was conducted. In Sierra Leone, of the 4,199 households interviewed in the LFS, 65.8 percent (2,764 households) recorded a cell phone number for the household head, and, of those, 80.0 percent responded to at least one round of the cell phone survey. The unweighted sample was 59.1 percent urban (2,483 households) and 40.9 percent rural (1,716 households). Of urban households, 81.4 percent (2,021 households) listed a cell phone number for the household head, and, of those, 88.1 percent (1,780 households) responded in at least one of the three rounds of the cell phone survey. Of rural households, 43.1 percent (740 households) listed a cell phone number for the household head, and, of those, 58.1 percent (430 households) responded in at least one of the three rounds.

Analysis unit

• Individual
• Household Head

Universe

All households from the 2014 Sierra Leone Labor Force Survey which provided cell phone numbers.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame for the cell phone survey was the Sierra Leone Labor Force Survey (LFS) 2014. The LFS is a nationally representative stratified cluster sample survey conducted in July and August 2014, and includes the oversampling of urban areas. As part of the LFS, a total of 4199 households in 280 enumeration areas were interviewed. Interviewers collected the phone number, if available, for the head of household, and 2,764 households interviewed in the LFS included phone numbers. All available numbers from the LFS were included in the cell phone survey. The phone numbers were reported for 43 percent of rural households and 82 percent of urban households. Those households reporting numbers are unevenly distributed across the sample though there is at least partial coverage in all districts, ranging from 93 percent in Freetown (Western urban) to 30 percent in Kailahun district.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

As the survey was administered by telephone, the length of the questionnaire was targeted as 20 to 25 minutes. In Round 1, the questionnaire focused on employment and labor market conditions, non-agricultural business operations, agricultural activity, food security, health responses (covering only fever and pregnancy), remittances, travel, trust and knowledge about Ebola. In Round 2, questions were added on social assistance and education on the radio, and there were small changes to the existing questions based on the results from Round 1.

Questions on earnings were revised to match the Labor Force Survey questions more closely, in particular to account for earnings that were expressed in time unit other than months, and questions on the incidence and treatment of child diarrhea were adding using identical wording to the Demographic and Health Survey (DHS). The most substantial changes were to the migration section as the Round 1 analysis found inconsistencies in the migration reporting. Details of these changes can be found in the Round 2 report. In Round 3, the agriculture, social assistance, and education sections were expanded while the trust section was dropped due to limited variation between Rounds 1 and 2.

The only questions on Ebola Virus Disease (EVD) specifically were in Round 1 and focused on whether the respondent had heard of Ebola and what were their main sources of information were. This section was placed at the end of the questionnaire in order to elicit unbiased responses in other sections, since people may be distrustful of the government especially regarding Ebola, at a time of such emergency.

Questions related directly to incidence of EVD within the household were excluded for two reasons. First EVD is a relatively rare event and the sample was unlikely to yield sufficient observations for meaningful analysis, and secondly, the respondents will be called repeatedly as part of the high frequency survey therefore it was necessary to avoid sensitive questions that may increase attrition in later rounds. The included questions were worded in such a way as to facilitate differences-in-differences comparisons. The vast majority of questions were identical in their wording to those asked during the LFS or other nationally representative surveys for which detailed data were available including the DHS, the National Public Services Survey (NPS) and the Agricultural Households Tracking Survey (AHTS).

In a few cases, the time period over which the questions were asked was shortened to make it relevant to the last few months during which the outbreak has been growing. For example, the NPS asked about remittances in the last year whereas in November 2014, respondents were asked about remittances received in the last month.

Cleaning operations

The datasets were cleaned and compiled by teams from Innovations for Poverty Action and the World Bank's Poverty Global Practice and Social Protection and Labor Global Practice.

Response rate

Overall the response rate was higher than expected given the nature of the survey and the difficult conditions under which it was conducted. In Sierra Leone, of the 4,199 households interviewed in the LFS, 65.8 percent (2,764 households) recorded a cell phone number for the household head, and, of those, 80.0 percent responded to at least one round of the cell phone survey.

The unweighted sample was 59.1 percent urban (2,483 households) and 40.9 percent rural (1,716 households). Of urban households, 81.4 percent (2,021 households) listed a cell phone number for the household head, and, of those, 88.1 percent (1,780 households) responded in at least one of the three rounds of the cell phone survey. Of rural households, 43.1 percent (740 households) listed a cell phone number for the household head, and, of those, 58.1 percent (430 households) responded in at least one of the three rounds.

Russia Number of Subscriber: Mobile Phone data was reported at 290,400.000 Unit th in Sep 2018. This records a decrease from the previous number of 291,600.000 Unit th for Jun 2018. Russia Number of Subscriber: Mobile Phone data is updated quarterly, averaging 254,962.700 Unit th from Mar 2005 (Median) to Sep 2018, with 55 observations. The data reached an all-time high of 291,700.000 Unit th in Sep 2017 and a record low of 82,000.000 Unit th in Mar 2005. Russia Number of Subscriber: Mobile Phone data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Global Database’s Russian Federation – Table RU.TG007: Number of Phones.

Snapshot img

Mobile Phone Market Size 2025-2029

The mobile phone market size is forecast to increase by USD 213.9 billion at a CAGR of 6.8% between 2024 and 2029.

The market is experiencing significant growth, driven primarily by the increasing adoption of smartphones. According to recent data, sales of mobile phones, particularly smartphones, through e-commerce platforms have surged, indicating a strong consumer demand. This trend is expected to continue as more consumers shift towards online shopping for convenience and accessibility. However, the market faces challenges related to security and privacy concerns with smartphone usage. With the increasing amount of personal data being stored and transmitted through mobile devices, there is a growing need for robust security measures to protect against cyber threats. Companies in the market must prioritize addressing these concerns through innovative solutions and transparent communication with consumers to build trust and maintain market competitiveness. Effective strategies for navigating these challenges include investing in advanced security features, implementing data protection policies, and providing clear and concise information to consumers about their privacy practices. By focusing on these key drivers and challenges, companies can capitalize on market opportunities and position themselves for long-term success in the market.

What will be the Size of the Mobile Phone Market during the forecast period?

Request Free SampleThe market continues to evolve at an unprecedented pace, with technological advancements and shifting consumer preferences shaping its dynamics. Optical and digital zoom capabilities enhance photographic experiences, while artificial intelligence (AI) and machine learning algorithms elevate user experience (UX) through personalized recommendations and seamless interactions. Mobile gaming gains traction, fueled by improved graphics and processing power. Fingerprint sensors and biometric authentication offer enhanced security, and image stabilization ensures crisp, clear images. Mobile hardware innovations, such as high refresh rates, push the boundaries of performance. The integration of AI, biometric authentication, and UX design continues to redefine mobile design, as mobile data, network, and advertising industries adapt to meet evolving consumer demands. Camera technology, mobile payments, app development, and streaming services further expand the market's reach, with augmented reality (AR) and virtual reality (VR) applications poised to revolutionize industries. Mobile marketing and wireless charging solutions cater to the growing need for convenience and connectivity. The mobile landscape remains a dynamic and ever-evolving ecosystem, with continuous innovation and adaptation shaping its future.

How is this Mobile Phone Industry segmented?

The mobile phone industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. Distribution ChannelOfflineOnlineTypeSmartphoneFeature phonePrice-RangeBudgetMid-RangePremiumOperating System AndroidiOSOthersGeographyNorth AmericaUSCanadaMexicoEuropeFranceGermanyItalySpainUKMiddle East and AfricaUAEAPACChinaIndiaJapanSouth KoreaSouth AmericaBrazilRest of World (ROW)

By Distribution Channel Insights

The offline segment is estimated to witness significant growth during the forecast period.In the dynamic the market, various entities shape consumer behavior and market trends. Social media platforms serve as a powerful tool for mobile marketing, enabling brands to engage with customers and promote their latest offerings. Mobile security remains a top priority, with mobile software providers continuously releasing updates to safeguard against threats. Mobile tariffs vary, offering consumers diverse pricing plans, including pay-as-you-go and monthly subscriptions. Feature phones cater to budget-conscious consumers, while fast charging and long battery life are desirable features for power users. Mobile operating systems, such as Android and iOS, dominate the market, providing a seamless user experience (UX) through mobile design and intuitive mobile apps. Virtual reality (VR) and augmented reality (AR) technologies offer immersive experiences, while optical zoom and digital zoom enhance camera capabilities. Artificial intelligence (AI) and machine learning integrate into mobile hardware, improving functionality and convenience. Biometric authentication, including fingerprint sensors and facial recognition, adds an extra layer of security. Mobile gaming, streaming services, and mobile payments cater to diverse consumer preferences. App development continues to evolve, with mobile advertising and data privacy becoming increasingly important considerations. Mobile service providers offer various plans

The number of smartphone users in the Philippines was forecast to increase between 2024 and 2029 by in total 5.6 million users (+7.29 percent). This overall increase does not happen continuously, notably not in 2026, 2027, 2028 and 2029. The smartphone user base is estimated to amount to 82.33 million users in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

No of Mobile Phone Subscribers: per 1000 Persons: UF: Tumen Region: ow Yamalo Nenetsky Area data was reported at 2.436 Unit th in 2023. This records a decrease from the previous number of 2.492 Unit th for 2022. No of Mobile Phone Subscribers: per 1000 Persons: UF: Tumen Region: ow Yamalo Nenetsky Area data is updated yearly, averaging 2.383 Unit th from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 2.787 Unit th in 2015 and a record low of 0.000 Unit th in 2000. No of Mobile Phone Subscribers: per 1000 Persons: UF: Tumen Region: ow Yamalo Nenetsky Area data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Transport and Telecommunications Sector – Table RU.TG009: Number of Mobile Phone Subscribers: per 1000 Persons: by Region.

The average time spent daily on a phone, not counting talking on the phone, has increased in recent years, reaching a total of * hours and ** minutes as of April 2022. This figure was expected to reach around * hours and ** minutes by 2024.

Abstract

To facilitate the use of data collected through the high-frequency phone surveys on COVID-19, the Living Standards Measurement Study (LSMS) team has created the harmonized datafiles using two household surveys: 1) the country’ latest face-to-face survey which has become the sample frame for the phone survey, and 2) the country’s high-frequency phone survey on COVID-19.

The LSMS team has extracted and harmonized variables from these surveys, based on the harmonized definitions and ensuring the same variable names. These variables include demography as well as housing, household consumption expenditure, food security, and agriculture. Inevitably, many of the original variables are collected using questions that are asked differently. The harmonized datafiles include the best available variables with harmonized definitions.

Two harmonized datafiles are prepared for each survey. The two datafiles are: 1. HH: This datafile contains household-level variables. The information include basic household characterizes, housing, water and sanitation, asset ownership, consumption expenditure, consumption quintile, food security, livestock ownership. It also contains information on agricultural activities such as crop cultivation, use of organic and inorganic fertilizer, hired labor, use of tractor and crop sales.
2. IND: This datafile contains individual-level variables. It includes basic characteristics of individuals such as age, sex, marital status, disability status, literacy, education and work.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

See “Malawi - Integrated Household Panel Survey 2010-2013-2016-2019 (Long-Term Panel, 102 EAs)” and “Malawi - High-Frequency Phone Survey on COVID-19” available in the Microdata Library for details.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

Malawi Integrated Household Panel Survey (IHPS) 2019 and Malawi High-Frequency Phone Survey on COVID-19 data were harmonized following the harmonization guidelines (see “Harmonized Datafiles and Variables for High-Frequency Phone Surveys on COVID-19” for more details).

The high-frequency phone survey on COVID-19 has multiple rounds of data collection. When variables are extracted from multiple rounds of the survey, the originating round of the survey is noted with “_rX” in the variable name, where X represents the number of the round. For example, a variable with “_r3” presents that the variable was extracted from Round 3 of the high-frequency phone survey. Round 0 refers to the country’s latest face-to-face survey which has become the sample frame for the high-frequency phone surveys on COVID-19. When the variables are without “_rX”, they were extracted from Round 0.

Response rate

See “Malawi - Integrated Household Panel Survey 2010-2013-2016-2019 (Long-Term Panel, 102 EAs)” and “Malawi - High-Frequency Phone Survey on COVID-19” available in the Microdata Library for details.

Abstract

The phone survey was conducted to gather data on the socio-economic impacts of COVID-19 crisis, as well as the Hunga Tonga-Hunga Ha'apai volcanic eruption and tsunami in Tonga. Round 1 interviewed 2,527 households both in urban and rural regions of the country from April 12, 2022, to May 7, 2022. Survey topics included employment and income, food security, coping strategies, access to health services, asset ownership, and preparedness. While these findings are not without their caveats due to the lack of baseline data, constraints of the mobile phone survey methodology, and data quality constraints, they represent the best estimates to date and supplement other data on macroeconomic conditions, exports, firm-level information, etc. to develop an initial picture of the impacts of the crises on the population.

Geographic coverage

Urban and rural areas.

Analysis unit

Household.

Universe

All respondents must be at least 18 years of age to undertake the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Tonga HFPS Round 1 sample was generated through a Random Digit Dialing (RDD) process covering all cell telephone numbers active at the time of the sample selection. The survey was administered by Sistemas Integrales.

The RDD methodology generates virtually all possible telephone numbers in the country under the national telephone numbering plan and then draws a random sample of numbers. This method guarantees full coverage of the population with a phone.

First, a large first-phase sample of cell phone numbers was selected and screened through an automated process to identify the active numbers. Then, a smaller second-phase sample was selected from the active residential numbers identified in the first-phase sample and was delivered to the data collection team to be called by the interviewers. When a cell phone was called, the call answerer was interviewed as long as he or she was 18 years of age or above and knowledgeable about the household activities.

It was initially planned to stratify the sample by island group based on the phone number prefixes. However, this was not feasible given the high internal migration across islands and the atypical assignment of phone number prefixes across islands in Tonga. The sample is overrepresenting urban areas and the population of Tongatapu.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire was developed in both English and Tongan. Sections of the Questionnaire: 1. Interview Information 2. Basic Information 3. Livelihood 4. Assets 5. Food Insecurity 6. Public Services 7. Coping Strategies 8. Preparedness 9. Recontact.

The questionnaire is provided in this documentation.

Cleaning operations

At the end of data collection, the raw dataset was cleaned by the survey firm and the World Bank team. Data cleaning mainly included formatting, relabeling, and excluding survey monitoring variables (e.g., interview start and end times). Data was edited using the software STATA.

Response rate

The survey interviewed 2,527 households with an unweighted phone response rate of 31.2%.

In 2021, the number of mobile users worldwide stood at 7.1 billion, with forecasts suggesting this is likely to rise to 7.26 billion by 2022. In 2025, the number of mobile users worldwide is projected to reach 7.49 billion.