In Patterns of Democracy, Arend Lijphart (1999) not only contends that democratic institutions cluster in two distinct forms, but also that consensus democracies—when contrasted with majoritarian arrangements—are “kinder, gentler” types of institutional settings (Lijphart 1999: 301-302). the present article reveals that Lijphart’s two dimensional map of democracy, although applicable to established democracies, does not apply equally well to post-communist countries. Nevertheless, multivariate empirical verification reveals that some elements included in the consensus democracy framework should be introduced in new constitutions, but perhaps not as the monolithic cluster of basic laws of constitutions originally suggested by Lijphart. Hence the present study casts a shadow on the relevance of the majoritarian versus consensus classification of democratic regimes.

Why might countries join alliances?United NationsUNESCO = United National Educational, Scientific, and Cultural Organization, http://en.unesco.org/FAO = Food and Agricultural Organization of the United Nations, http://www.fao.org/home/en/WHO = World Health Organization, http://www.who.int/en/European UnionEU = European UnionSchengen = Countries who are members of the Schengen Area which guarantees freedom of movement to EU citizens and the right to travel and work and live in any EU countries.FrancophoneCountries that have French as an official language? The map depicts the countries that are members of the International Organisation of La Francophonie listed on their official website. Only the 57 member states and governments are included. There are 23 observer states throughout the world. Cape Verde Islands is a member, but not included on the map.Organization of Petroleum Exporting Countries (OPEC)Indonesia reactivated its membership in OPEC in January of 2016.Oil production data from http://www.opec.org/opec_web/static_files_project/media/downloads/publications/MOMR%20June%202016.pdfAfrican Union (AU)founded by 32 countries in Addis Ababa, Ethiopia on May 25, 1963Membership in the African Union from http://www.au.int/en/AU_Member_StatesMorocco is not a member of the African Union because it opposed the membership of Western Sahara, Sahrawi Arab Democratic Republic. It is not shown on the map, but did join the AU on February 27, 1976.Other OrganizationsIMF = International Monetary Fund, http://www.imf.org/external/index.htmIBRD = International Bank for Reconstruction and Development (World Bank), http://www.worldbank.org/en/about/what-we-do/brief/ibrdIAEA = International Atomic Energy Agency, https://www.iaea.org/WMO = World Meteorological Organization, http://public.wmo.int/en

The Administrative Boundaries used by the Data in Emergencies Hub are the result of a collection of international and subnational divisions currently used by FAO country offices for mapping and reporting purposes. With only a few exceptions, they are mostly derived from datasets published on The Humanitarian Data Exchange (OCHA).The dataset consists of national boundaries, first subdivision, and second subdivision for Sure! Here's the reformatted list as requested:

Afghanistan, Angola, Bangladesh, Burkina Faso, Burundi, Cambodia, Cameroon, Central African Republic, Chad, Colombia, Comoros, Democratic Republic of the Congo, Ecuador, El Salvador, Federated States of Micronesia, Ghana, Guatemala, Haiti, Honduras, Iraq, Kingdom of Tonga, Kiribati, Kyrgyzstan, Lao People's Democratic Republic, Lebanon, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mozambique, Myanmar, Namibia, Nepal, Niger, Nigeria, Pakistan, Palestine, Philippines, Republic of the Marshall Islands, Saint Lucia, Samoa, Senegal, Sierra Leone, Solomon Islands, Somalia, South Sudan, Sri Lanka, Sudan, Suriname, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Togo, Tuvalu, Uganda, Ukraine, Venezuela, Vietnam, Yemen, and Zimbabwe.In the Feature Layer, the administrative boundaries are represented by closed polygons, administrative levels are nested and multiple distinct polygons are represented as a single record.The Data in Emergencies Hub team is responsible for keeping the layer up to date, so please report any possible errors or outdated information.The boundaries and names shown and the designations used on these map(s) do not imply the expression of any opinion whatsoever on the part of FAO concerning the legal status of any country, territory, city, or area or of its authorities, or concerning the delimitation of its frontiers and boundaries. Dashed lines on maps represent approximate border lines for which there may not yet be full agreement. The final boundary between the Sudan and South Sudan has not yet been determined. The final status of the Abyei area is not yet determined. The dotted line represents approximately the Line of Control in Jammu and Kashmir agreed upon by India and Pakistan. The final status of Jammu and Kashmir has not yet been agreed upon by the parties.

Why might countries join alliances?United NationsUNESCO = United National Educational, Scientific, and Cultural Organization, http://en.unesco.org/FAO = Food and Agricultural Organization of the United Nations, http://www.fao.org/home/en/WHO = World Health Organization, http://www.who.int/en/European UnionEU = European UnionSchengen = Countries who are members of the Schengen Area which guarantees freedom of movement to EU citizens and the right to travel and work and live in any EU countries.FrancophoneCountries that have French as an official language? The map depicts the countries that are members of the International Organisation of La Francophonie listed on their official website. Only the 57 member states and governments are included. There are 23 observer states throughout the world. Cape Verde Islands is a member, but not included on the map.Organization of Petroleum Exporting Countries (OPEC)Indonesia reactivated its membership in OPEC in January of 2016.Oil production data from http://www.opec.org/opec_web/static_files_project/media/downloads/publications/MOMR%20June%202016.pdfAfrican Union (AU)founded by 32 countries in Addis Ababa, Ethiopia on May 25, 1963Membership in the African Union from http://www.au.int/en/AU_Member_StatesMorocco is not a member of the African Union because it opposed the membership of Western Sahara, Sahrawi Arab Democratic Republic. It is not shown on the map, but did join the AU on February 27, 1976.Other OrganizationsIMF = International Monetary Fund, http://www.imf.org/external/index.htmIBRD = International Bank for Reconstruction and Development (World Bank), http://www.worldbank.org/en/about/what-we-do/brief/ibrdIAEA = International Atomic Energy Agency, https://www.iaea.org/WMO = World Meteorological Organization, http://public.wmo.int/en

Abstract

Round 1 of the Afrobarometer survey was conducted from July 1999 through June 2001 in 12 African countries, to solicit public opinion on democracy, governance, markets, and national identity. The full 12 country dataset released was pieced together out of different projects, Round 1 of the Afrobarometer survey,the old Southern African Democracy Barometer, and similar surveys done in West and East Africa.

The 7 country dataset is a subset of the Round 1 survey dataset, and consists of a combined dataset for the 7 Southern African countries surveyed with other African countries in Round 1, 1999-2000 (Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe). It is a useful dataset because, in contrast to the full 12 country Round 1 dataset, all countries in this dataset were surveyed with the identical questionnaire

Geographic coverage

Botswana Lesotho Malawi Namibia South Africa Zambia Zimbabwe

Analysis unit

Basic units of analysis that the study investigates include: individuals and groups

Kind of data

Sample survey data [ssd]

Sampling procedure

A new sample has to be drawn for each round of Afrobarometer surveys. Whereas the standard sample size for Round 3 surveys will be 1200 cases, a larger sample size will be required in societies that are extremely heterogeneous (such as South Africa and Nigeria), where the sample size will be increased to 2400. Other adaptations may be necessary within some countries to account for the varying quality of the census data or the availability of census maps.

The sample is designed as a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of selection for interview. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible. A randomly selected sample of 1200 cases allows inferences to national adult populations with a margin of sampling error of no more than plus or minus 2.5 percent with a confidence level of 95 percent. If the sample size is increased to 2400, the confidence interval shrinks to plus or minus 2 percent.

Sample Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

Sample Design

The sample design is a clustered, stratified, multi-stage, area probability sample.

To repeat the main sampling principle, the objective of the design is to give every sample element (i.e. adult citizen) an equal and known chance of being chosen for inclusion in the sample. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible.

In a series of stages, geographically defined sampling units of decreasing size are selected. To ensure that the sample is representative, the probability of selection at various stages is adjusted as follows:

The sample is stratified by key social characteristics in the population such as sub-national area (e.g. region/province) and residential locality (urban or rural). The area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. And the urban/rural stratification is a means to make sure that these localities are represented in their correct proportions. Wherever possible, and always in the first stage of sampling, random sampling is conducted with probability proportionate to population size (PPPS). The purpose is to guarantee that larger (i.e., more populated) geographical units have a proportionally greater probability of being chosen into the sample. The sampling design has four stages

A first-stage to stratify and randomly select primary sampling units;

A second-stage to randomly select sampling start-points;

A third stage to randomly choose households;

A final-stage involving the random selection of individual respondents

We shall deal with each of these stages in turn.

STAGE ONE: Selection of Primary Sampling Units (PSUs)

The primary sampling units (PSU's) are the smallest, well-defined geographic units for which reliable population data are available. In most countries, these will be Census Enumeration Areas (or EAs). Most national census data and maps are broken down to the EA level. In the text that follows we will use the acronyms PSU and EA interchangeably because, when census data are employed, they refer to the same unit.

We strongly recommend that NIs use official national census data as the sampling frame for Afrobarometer surveys. Where recent or reliable census data are not available, NIs are asked to inform the relevant Core Partner before they substitute any other demographic data. Where the census is out of date, NIs should consult a demographer to obtain the best possible estimates of population growth rates. These should be applied to the outdated census data in order to make projections of population figures for the year of the survey. It is important to bear in mind that population growth rates vary by area (region) and (especially) between rural and urban localities. Therefore, any projected census data should include adjustments to take such variations into account.

Indeed, we urge NIs to establish collegial working relationships within professionals in the national census bureau, not only to obtain the most recent census data, projections, and maps, but to gain access to sampling expertise. NIs may even commission a census statistician to draw the sample to Afrobarometer specifications, provided that provision for this service has been made in the survey budget.

Regardless of who draws the sample, the NIs should thoroughly acquaint themselves with the strengths and weaknesses of the available census data and the availability and quality of EA maps. The country and methodology reports should cite the exact census data used, its known shortcomings, if any, and any projections made from the data. At minimum, the NI must know the size of the population and the urban/rural population divide in each region in order to specify how to distribute population and PSU's in the first stage of sampling. National investigators should obtain this written data before they attempt to stratify the sample.

Once this data is obtained, the sample population (either 1200 or 2400) should be stratified, first by area (region/province) and then by residential locality (urban or rural). In each case, the proportion of the sample in each locality in each region should be the same as its proportion in the national population as indicated by the updated census figures.

Having stratified the sample, it is then possible to determine how many PSU's should be selected for the country as a whole, for each region, and for each urban or rural locality.

The total number of PSU's to be selected for the whole country is determined by calculating the maximum degree of clustering of interviews one can accept in any PSU. Because PSUs (which are usually geographically small EAs) tend to be socially homogenous we do not want to select too many people in any one place. Thus, the Afrobarometer has established a standard of no more than 8 interviews per PSU. For a sample size of 1200, the sample must therefore contain 150 PSUs/EAs (1200 divided by 8). For a sample size of 2400, there must be 300 PSUs/EAs.

These PSUs should then be allocated proportionally to the urban and rural localities within each regional stratum of the sample. Let's take a couple of examples from a country with a sample size of 1200. If the urban locality of Region X in this country constitutes 10 percent of the current national population, then the sample for this stratum should be 15 PSUs (calculated as 10 percent of 150 PSUs). If the rural population of Region Y constitutes 4 percent of the current national population, then the sample for this stratum should be 6 PSU's.

The next step is to select particular PSUs/EAs using random methods. Using the above example of the rural localities in Region Y, let us say that you need to pick 6 sample EAs out of a census list that contains a total of 240 rural EAs in Region Y. But which 6? If the EAs created by the national census bureau are of equal or roughly equal population size, then selection is relatively straightforward. Just number all EAs consecutively, then make six selections using a table of random numbers. This procedure, known as simple random sampling (SRS), will

Abstract

This research is a survey of unregistered businesses conducted in The Democratic Republic of the Congo (DRC) between June 7 and June 21, 2010, at the same time with The Democratic Republic of the Congo 2010 Enterprise Survey. Data from 150 enterprises were analyzed.

Questionnaire topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. The mode of data collection is face-to-face interviews.

The Informal Surveys aim to accomplish the following objectives: 1) To provide information about the state of the private sector for informal businesses in client countries; 2) To generate information about the reasons of said informality; 3) To collect useful data for the research agenda on informality; 4) To provide information on the level of activity in the informal sector of selected urban centers in each country.

Geographic coverage

National

Analysis unit

The primary sampling unit of the Informal Surveys is an unregistered establishment. For DRC, informal firms were defined as those not registered with the Fédération Entreprises du Congo (FEC) and Confédération des Petites et Moyennes Entreprises du Congo (COPEMECO).

Universe

The whole population, or the universe, covered in the survey is the non-agricultural informal economy.

At the beginning of each survey, a screening procedure is conducted in order to identify eligible interviewees. At this point, a full description of all the activities of the business owner or manager is taken; based on its principal activity, a business is then classified in the manufacturing or services stratum using a list of activities developed from previous iterations of the survey. Certain activities are excluded such as strictly illegal activities (e.g., prostitution or drug trafficking) as well as individual activities that are forms of selling labor like domestic servants or windshield washers.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Informal Surveys are conducted in selected urban centers, which are intended to coincide with the locations for the implementation of the main Enterprise Surveys. The overall number of interviews is pre-determined.

In The Democratic Republic of the Congo, the urban centers identified were Kinshasa, Kisangani, Lubumbashi, and Matadi. At the outset, the target sample in Kinshasa was 60 interviews, in Kisangani - 30 interviews, in Lubumbashi - 40 interviews, and in Matadi was 20 interviews. The sample will be confined to the major cities covered in the running in parallel enterprise survey of the formal economy. The target number of interviews will reflect, as far as practical, the individuals' population distribution but with no more than 60% sample from a single city and no city with fewer than 20 interviews in total.

Sampling in the Informal Surveys is conducted within clearly delineated sampling zones, which are geographically determined divisions within each urban center. Sampling zones are defined at the beginning of fieldwork, and are delineated according to the concentration and geographical dispersion of informal business activity. After the sampling sizes are defined for each location, every city is divided into several zones that may or may not correspond to the administrative districts.

The zones are selected using local knowledge (information about the districts/parts of the city where most of the informal businesses are located).

The number of zones depends on the sample size for this geographic location. For example, if in a particular city there are 40 planned informal interviews (20 manufacturing and 20 services) in the city should have 10 zones (4 interviews per zone including 2 manufacturing and 2 services firms).

In DRC, using Google maps or local city maps, the target areas within each city were identified. With input from the local agency applying local knowledge, the starting points were defined. The number of zones was determined by the target sample size for each city divided by the cluster size (4 interviews). This is the only element of the sample selection where there is local influence.

In Kinshasa, for a total of 60 interviews, 15 sampling zones were initially identified (60/4=15 zones). In Lubumbashi, a total of 40 interviews yielded 10 sampling zones (40/4 = 10 zones). In Matadi, a total of 20 interviews yielded 5 sampling zones (20/4 = 5 zones). In Kinsangani, only 6 sampling zones were drawn and some zones were over or under sampled. As described above, the criteria used in choosing these sample sectors was a combination of territorial dispersion and the presence of informal businesses.

In order to provide information on diverse aspects of the informal economy, the sample is designed to have equal proportions of services and manufacturing (50:50). These sectors are defined by responses provided by each informal business to a question on the business's main activity included in the screener portion of the questionnaire. Manufacturing activity in the informal sector includes business activity requiring inputs and/or intermediate goods. Thus, for example, the processing of coffee, sugar, oil, dried fruit, or other processed foods is considered manufacturing, while the simple selling of these goods falls under services. If an informal business conducts a mixture of these activities, the business is considered under the manufacturing stratum.

In order to ensure a degree of geographical dispersion within each sampling zone, two starting points were identified. Each starting point is marked on the map and is usually located at a major intersection or other prominent point at the edge of a zone. The road(s) that the interviewer should follow and the direction the interviewer should take is also marked on the map created by the local consultant.

Each sampling zone, including its two starting points, were marked using Google maps, with the GPS coordinates of the starting points being systematically recorded. Additionally, when obtaining a complete interview, the exact address of the informal business (or where the interview took place) was registered by the interviewer. Once in the office, this address was searched in Google maps, and its GPS coordinates were registered in a fieldwork report.

If no address was immediately available, using local knowledge, the GPS coordinates were determined using imaging via Google maps. In order to preserve confidentiality, the exact coordinates of businesses are not published.

Due to issues of non-response, in the process of fieldwork, the implementing contractor was unable to obtain the targeted four interviews in each of the originally delineated sectors.

As a result, replacement sectors were delineated, ex post. Additionally, the implementing contractor noted that in various interviews there were notable shortfalls in response rates to certain questions. For these reasons, additional interviews were authorized. These were distributed according to the discretion of the implementing contractor in DRC, with authorization from the World Bank.

In sum, there were 36 zones in DRC; Kinshasa (15 zones), Kisangani (6 zones), Lubumbashi (10 zones), and Matadi (5 zones).

Complete information regarding the sampling methodology can be found in "Description of The Democratic Republic of the Congo Informal Survey Implementation" in "Technical Documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Informal Questionnaire.

The survey topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration.

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.