The General Social Surveys (GSS) have been conducted by the "https://www.norc.org/Pages/default.aspx" Target="_blank">National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. The 2016-2020 GSS consisted of re-interviews of respondents from the 2016 and 2018 Cross-Sectional GSS rounds. All respondents from 2018 were fielded, but a random subsample of the respondents from 2016 were released for the 2020 panel. Cross-sectional responses from 2016 and 2018 are labelled Waves 1A and 1B, respectively, while responses from the 2020 re-interviews are labelled Wave 2.

The 2016-2020 GSS Wave 2 Panel also includes a collaboration between the General Social Survey (GSS) and the "https://electionstudies.org/" Target="_blank">American National Election Studies (ANES). The 2016-2020 GSS Panel Wave 2 contained a module of items proposed by the ANES team, including attitudinal questions, feelings thermometers for presidential candidates, and plans for voting in the 2020 presidential election. These respondents appear in both the ANES post-election study and the 2016-2020 GSS panel, with their 2020 GSS responses serving as their equivalent pre-election data. Researchers can link the relevant GSS Panel Wave 2 data with ANES post-election data using either ANESID (in the GSS Panel Wave 2 datafile) or V200001 in the ANES 2020 post-election datafile.

This file contains all of the cases and variables that are in the original 2014 General Social Survey, but is prepared for easier use in the classroom. Changes have been made in two areas. First, to avoid confusion when constructing tables or interpreting basic analysis, all missing data codes have been set to system missing. Second, many of the continuous variables have been categorized into fewer categories, and added as additional variables to the file.

The General Social Surveys (GSS) have been conducted by the National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. This data file has all cases and variables asked on the 2014 GSS. There are a total of 3,842 cases in the data set but their initial sampling years vary because the GSS now contains panel cases. Sampling years can be identified with the variable SAMPTYPE.

To download syntax files for the GSS that reproduce well-known religious group recodes, including RELTRAD, please visit the "/research/syntax-repository-list" Target="_blank">ARDA's Syntax Repository.

The General Social Surveys (GSS) have been conducted by the National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. This data file has all cases and variables asked on the 2014 GSS. There are a total of 3,842 cases in the data set but their initial sampling years vary because the GSS now contains panel cases. Sampling years can be identified with the variable SAMPTYPE.

To download syntax files for the GSS that reproduce well-known religious group recodes, including RELTRAD, please visit the "/research/syntax-repository-list" Target="_blank">ARDA's Syntax Repository.

Longitudinal or panel surveys offer unique benefits for social science research, but they typically suffer from attrition, which reduces sample size and can result in biased inferences. Previous research tends to focus on the demographic predictors of attrition, conceptualizing attrition propensity as a stable, individual- level characteristic—some individuals (e.g., young, poor, residentially mobile) are more likely to drop out of a study than others. We argue that panel attrition reflects both the characteristics of the individual respondent as well as her survey experience, a factor shaped by the design and implementation features of the study. In this paper, we examine and compare the predictors of panel attrition in the 2008-2009 American National Election Study, an on- line panel, and the 2006-2010 General Social Survey, a face-to-face panel. In both cases, survey experience variables are predictive of panel attrition above and beyond the standard demographic predictors, but the particular measures of relevance differ across the two surveys. The findings inform statistical corrections for panel attrition bias and provide study design insights for future panel data collections.

The General Social Surveys have been conducted during February, March, and April of 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1980, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1993, 1994, 1996, 1998, 2000, 2002, 2004, 2006, and 2008. There are a total of 53,043 completed interviews (1,613 in 1972, 1,504 in 1973, 1,484 in 1974, 1,490 in 1975, 1,499 in 1976, 1,530 in 1977, 1,532 in 1978, 1,468 in 1980, 1,506 in 1982, 354 in 1982 black oversample, 1,599 in 1983, 1,473 in 1984, 1, 534 in 1985, 1,470 in 1986, 1466 in 1987, 353 in 1987 black oversample, 1481 in 1988, 1,537 in 1989, 1372 in 1990, 1,517 in 1991, 1,606 in 1993, 2,904 in 1996, 2,832 in 1998, 2,817 in 2000, 2,765 in 2002, 2,812 in 2004, 4510 in 2006, and 2023 in 2008). The median length of the interview has been about one and a half hours. Each survey from 1972 to 2004 was an independently drawn sample of English-speaking persons 18 years of age or over, living in non-institutional arrangements within the United States. Starting in 2006 Spanish-speakers were added to the target population. Block quota sampling was used in 1972, 1973, and 1974 surveys and for half of the 1975 and 1976 surveys. Full probability sampling was employed in half of the 1975 and 1976 surveys and the 1977, 1978, 1980, 1982-1991, 1993-1998, 2000, 2002, 2004, 2006, and 2008 sur veys. Also, the 2004, 2006, and 2008 surveys had sub-sampled non-respondents This cumulative data set merges all 27 surveys into a single file with each year or survey acting as a subfile. This greatly simplifies the use of the General Social Surveys for both trend analysis and pooling. In addition, this cumulative data set contains newly created variables (e.g. a poverty line code). Finally, the cumulative file contains certain items never before available. In 2008 the GSS is in transition from a replicating cross-sectional design to a design that uses ro tating panels. There were two components: a new 2008 cross-section with 2,023 cases and the first reinterviews with 1,536 respondents from the 2006 GSS. In 2010 the new design will be fully implemented. There will be a new cross-section of about 2,000 cases, the first reinterviews of the 2008 GSS respondents, and the second and final reinterviews of the 2006 GSS respondents. In 2012 and later years this design will be repeated. Each GSS will thus 1) start a new 4-year/3-wave panel, 2) be in the middle of a 4-year/3-wave panel, and 3) finish a still earlier 4-year/3-wave panel.

This file differs from the General Social Survey 2014 in that all inapplicable values are set to system missing. The General Social Surveys (GSS) have been conducted by the National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. This data file has all cases and variables asked on the 2014 GSS. There are a total of 3,842 cases in the data set but their initial sampling years vary because the GSS now contains panel cases. Sampling years can be identified with the variable SAMPTYPE.

To download syntax files for the GSS that reproduce well-known religious group recodes, including RELTRAD, please visit the "/research/syntax-repository-list" Target="_blank">ARDA's Syntax Repository.

Abstract

The data is created from two firm censuses, both conducted by the Ghana Statistical Service. These were the 2003 NIC and the 2014 IBES. Identifying information on these firms such as firm name, firm locations, contact person, contact number etc were sourced from GSS for IBES 2014 and from Francis Teal for NIC 2003. This information was used to match firms over the 2 waves. The creation of the panel was funded by the Project for Enterprise Development in Low Income Countries (PEDL) and was undertaken by Andrew Kerr and Bruce McDougall of DataFirst, University of Cape Town

Geographic coverage

This panel is a handful of firms we found that were interviewed in both 2003 and 2014 - it is not geographically representative.

Analysis unit

Establishments

Universe

Establishments in Ghana.

Sampling procedure

This dataset is a panel derived from matching firms that were included in two Ghanaian censuses, NIC 2003 and IBES 2014. Each of these censuses had two phases.

2014 IBES Phase 1 was a census of non-household establishments with a fixed site and any household-based business with a sign indicating its presence within a household. Phase 2 was a stratified roughly 5% sample of the phase 1 firms. NIC 2003 Phase 1 was a census of non-household establishments with a fixed site and any household-based business with a sign indicating its presence within a household. Phase 2 was a stratified sample. All establishments with 10 or more persons engaged were enumerated and 5% firms with less than 10 persons engaged were sampled for phase 2. The phase 1 data was used to match firms across 2003 NIC and 2014 IBES and create the panel. This matching is likely to be non-random and a function of observable and unobservable characteristics. Thus the panel SHOULD NOT be considered a random sample of establishments alive in both 2003 and 2014.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

A detailed guide on how the NIC and IBES firms were matched using fuzzy algorithms has been uploaded for the users reference.

Data appraisal

The main data quality issue that users should be aware of is that these firms were matched using fuzzy logic - not all the matches are strong matches and some might be false matches.

Abstract

The Annual Household Income and Expenditure Survey (AHIES) is the first nationally representative high-frequency household panel survey in Ghana. The AHIES is being conducted to obtain quarterly and annual data on household final consumption expenditure and a wide scope of demographic, economic and welfare variables including statistics on labour, food security, multi-dimensional poverty and health status for research, policy, and planning. Some of the key macroeconomic indicators to be generated include quarterly GDP, regional GDP, quarterly unemployment, underemployment, inequality, consumption expenditure poverty, multidimensional poverty and food security. The data from the AHIES is classified, tabulated and disseminated so that researchers, administrators, policy makers and development partners can use the information in formulating and implementing various development programs at the national and community levels and also to monitor targets under the Sustainable Development Goals.

Geographic coverage

Nation - Wide

Analysis unit

Individuals, Households

Universe

The universe covers the population living within individual households in Ghana. However, such population which is defined as institutionalised population as persons living at elderly houses, rest homes, correction facilities, military baracks, and hospitals with special characteristics, nursery,and also nomadic population are excluded.

Sampling procedure

With the sampling procedure, 10,800 households in 600 EAs, consisting of 304 (50.67%) urban and 296 (49.33%) rural households were drawn from the 2021 Population and Housing Census listing frame to form the secondary sampling units. A random sampling methodology was adopted to select eighteen (18) households per selected EAs in all regions to form the full sample for the fieldwork to be able to produce regionally representative expenditures for GDP.

Mode of data collection

Computer Assisted Personal Interview [CAPI]

Abstract

The survey was conducted in Ghana between December 2012 and July 2014 as part of the Africa Enterprise Survey 2013 roll-out, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises 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.

Data from 720 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and 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 percent 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.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an 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 private 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. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Ghana was selected using stratified random sampling. Three levels of stratification were used in this country: firm sector, firm size, and geographic region.

Industry stratification was designed in the way that follows: the universe was stratified into four manufacturing industries (food, textiles and garments, chemicals and plastics, other manufacturing) and two service sectors (retail and other services).

Size stratification was defined following the standardized definition for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees).

Regional stratification for the Ghana ES was defined in four regions: Accra, North (Kumasi and Tamale), Takoradi, and Tema.

For the Ghana ES, several sample frames were used. The first was supplied by the World Bank and consists of enterprises interviewed in Ghana 2007. The World Bank required that attempts should be made to re-interview establishments responding to the Ghana 2007 survey where they were within the selected geographical regions and met eligibility criteria. Due to the fact that the previous round of surveys seemed to have utilized different stratification criteria (or no stratification at all) and due to the prevalence of small firms and firms located in the capital city in the 2007 sample the following convention was used. The presence of panel firms was limited to a maximum of 50% of the achieved interviews in each cell. That sample is referred to as the Panel.

The second frame was constructed using different lists acquired from relevant institutions in Ghana. The main lists used were obtained from the Ghana Statistical Service (GSS). These include: 1) The 2012 Firm Registry. The registry lacked information on firm employee size. 2) The list of firms paying VAT. The VAT dataset included a variable on firms; turnover. The VAT dataset and Firm Registry were merged by using the firms' identification number (TIN). VAT information was not available for all firms in the Firm Registry. 3) The list of Large Tax Payers. The Large Tax Payers file also lacked information on firm employee size.

Since firm size was missing from all lists mentioned above, after having discussed with GSS and with the local contractor the following methods were used to predict firm size. - All firms who were in the Firm Registry but not in the VAT dataset were considered to be micro firms and therefore not use in the current survey. - Firms who were in the Firm Registry and in the VAT dataset were considered to be small firms. - Firms in the Large Tax Payers dataset were considered medium or large firms. The original design was divided into two size groups: small firms and medium and large firms.

During fieldwork the GSS lists proved to be very inaccurate and not sufficient to reach the target sample design, As such they were complemented with additional lists of firms from the Ghana Chamber of Commerce and Industry and Business Associations. The list from the Ghana Chamber of Commerce lacked information on firm employee size or firm turnover. 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 1.3% (26 out of 1,990 establishments).

Finally, a block enumeration was also undertaken in order to build an additional list. The block enumeration allowed to physically creating a list of establishments from which to sample from. A total of 41 blocks were enumerated in the four locations included in the project out of the total 804 blocks identified. The enumeration was conducted without major problems in the time planned. The list of enumerated firms contained 958 records eligible for main Enterprise Survey.

Note: Unlike the standard ES, the universe for the Ghana ES is characterized by the presence of 5 size categories. The category medium&large was added as stratum in order to sample from the GSS large payers list, while the category "unknow size" was included in order to sample the firms in the Chamber of Commerce and Industry list.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Manufacturing Module Questionnaire - Services Module Questionnaire

The survey is fielded via manufacturing or services questionnaires in order not to 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.

There is a skip pattern in the Service Module Questionnaire for questions that apply only to retail firms.

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

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve

The National Congregations Study (NCS) dataset fills a void in the sociological study of congregations by providing data that can be used to draw a nationally aggregate picture of congregations. Thanks to innovations in sampling techniques, the 1998 NCS data was the first nationally representative sample of American congregations. Subsequent NCS waves were conducted in 2006-07, 2012, and 2018-19.

Like Wave II, Wave IV again included a panel component. In addition to the new cross-section of congregations generated in conjunction with the 2018 GSS, the NCS-IV included all Wave III congregations that were nominated by GSS respondents who participated in the GSS for the first time in 2012. That is, the panel did not include Wave III congregations that had been nominated by GSS respondents who were in the 2012 GSS because they were part of the GSS's own panel of re-interviewees. The 2018-19 NCS, then, includes a subset of congregations that also were interviewed in 2012. A full codebook, prepared by the primary investigator and containing a section with details about the panel datasets, is available for download "https://sites.duke.edu/ncsweb/files/2020/09/NCS-I-IV-Cumulative-Codebook_FINAL_8Sept2020.pdf" Target="_blank">here. The codebook contains the original questionnaire, as well as detailed information on survey methodology, weights, coding, and more.

The "/data-archive?fid=NCSIV" Target="_blank">NCS Cumulative Dataset is also available from the ARDA.