Pew Research Center

FOR RELEASE NOVEMBER 6, 2014

Crime and Corruption Top Problems in Emerging and Developing Countries

Most National Institutions Respected, Especially Military

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RECOMMENDED CITATION

Pew Research Center, November 2014, "Crime and Corruption Top Problems in Emerging and Developing Countries"

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Table of contents

  • About Pew Research Center
  • Crime and Corruption Top Problems in Emerging and Developing Countries
  • Methods in Detail

Crime and Corruption Top Problems in Emerging and Developing Countries

Most National Institutions Respected, Especially Military

People in Latin America, Africa, Asia and the Middle East all see crime and corruption as the greatest problems in their countries, according to the Pew Research Center survey.

[tweetable url="http://pewrsr.ch/CntryIssues2014" alt="Crime, corruption and poor quality schools are considered growing problems in emerging and developing countries"]

In nearly all these countries, the list of key challenges exist alongside economic problems including jobs, rising prices and public debt (see Global Public Downbeat about Economy, published September 9, 2014).

Most National Institutions Rated Positively, Especially Military

When asked to rate key institutions in their countries, people generally assign high marks to the military, with a median of 79% saying it has a good influence on the way things are going in their country. But most major national organizations and groups, such as the media, religious leaders, banks, corporations, the national government and civil servants also get positive marks. Emerging and developing publics are less enamored with their court systems – the only institution polled which receives support from less than half of respondents.

Overall, there have been only slight changes in views of these national groups and institutions since 2007, but within a few countries there have been dramatic swings in opinion. For instance, in Turkey, where President Erdogan has made weakening the influence of the military on civilian government a top priority, support for the armed forces has sharply declined in the last seven years.

[tweetable url="http://pewrsr.ch/CntryIssues2014" alt="In the Middle East, a median of just 40% say religious leaders are having a good influence on their country"]

[tweetable url="http://pewrsr.ch/CntryIssues2014" alt="Double-digit gain in ratings for religious leaders in Argentina since 2007, after Pope Francis elevated"]

These are among the findings of a recent survey by the Pew Research Center, conducted in 34 countries among 38,620 respondents from March 17 to June 5, 2014.

Top Country Problems: Crime and Corruption

Crime is seen as a very big problem by a median of 83% across the 34 emerging and developing economies surveyed. In 19 of these nations, crime is either tied for or holds the top spot among the nine problems tested. Law-breaking is more of an issue in Latin America (a median of 86% say it is a very big problem) and Africa (84%) than it is in Asia (72%) and the Middle East (67%). Crime is a lesser issue in the three Eastern Europe countries surveyed – less than half in Russia (47%), Ukraine (37%) and Poland (31%) see it as a top problem.

Many Worry about Crime, Corruption, Health Care, Poor Schools and Pollution

A median of 76% across 34 countries say corrupt political leaders are a very big problem in their country. This comprises the top spot in 10 of the countries surveyed, including in China, where 54% say corrupt officials are a big concern. Africans are far and away the most concerned about corruption (a median of 85%), but this issue also resonates broadly in other regions, including Eastern Europe. In Russia and Ukraine, 65% and 73% respectively cite corrupt political leaders as a top problem.

A median of 59% across emerging and developing markets say health care is a very big concern. Generally, Latin Americans, Africans and Middle Easterners are more worried about health care than Asian publics.

[tweetable url="http://pewrsr.ch/CntryIssues2014"]A median of 76% across 34 countries say corrupt political leaders are a very big problem in their country.

While no emerging country cites poor quality schools as its greatest problem, a median of 56% are very worried about this issue. Concern is greatest in Africa and Latin America. And a global median of 54% rate both water and air pollution as a very big problem. Pollution is one of the top problems cited in Latin America, and six-in-ten Middle Easterners rank water pollution as a very big concern.

A median of 50% across the emerging and developing nations surveyed say food safety is a pressing issue. Concern for the safety of food is greater in the Middle East and Latin America compared to Africa and Asia.

Growing Problems: Crime, Corruption, Schools

Crime, Corruption and Poor Quality Schools Growing Problem

There has been an overall increase in concern about the problems of crime, corrupt officials and poor quality schools in the emerging and developing nations surveyed in 2007 and 2014. For instance, in 2007, a median of 64% said crime was a very big problem across those 20 countries, but in 2014, 74% do. An almost identical change has occurred for the problem of corruption. And in 2007, a median of only 38% across these countries named poor quality schools as a big concern. Now, about half say this.

Many African countries are increasingly worried about crime, as are publics in Mexico and Argentina. All have seen double digit increases in concern about crime since 2007.

[tweetable url="http://pewrsr.ch/CntryIssues2014" alt="In South Africa, worries about crime have dropped from a nearly unanimous 96% in 2002 to a still-high 74% today"]

[tweetable url="http://pewrsr.ch/CntryIssues2014" alt="In China, there has been a 15 percentage point increase in worries about corrupt officials since 2008"]

On the contrary, worries about corruption in Poland have plummeted since 2002, when 70% named it as a very big problem. Only 46% say the same today.

In Africa, increasing numbers cite poor quality schools as a top problem in Ghana (+33 percentage points), Tanzania (+32), Uganda (+30) and Kenya (+19) since 2007. There also has been a rise in worries in Malaysia, Chile (which recently saw large-scale protests by students pushing for education reform), the Palestinian territories, Mexico and China. (For more on Mexican views of education, see Mexican President Peña Nieto’s Ratings Slip with Economic Reform, published August 26, 2014).

Military and Media Get Good Ratings; Views of Court System Mixed

Across the emerging and developing countries surveyed, people rate the military as the most positive national institution.1 Overall, a median of 79% say the military is a good influence on the way things are going in their country, while only 18% say it is a bad influence. Asians are the most supportive of their military, but publics in Africa the Middle East and Latin America all say the armed forces are a good influence on their country.

[tweetable url="http://pewrsr.ch/CntryIssues2014" alt="People in a few Latin American countries, where military coups were once common, are skeptical of the armed forces"]

[tweetable url="http://pewrsr.ch/CntryIssues2014" alt="In Russia, support for the military jumped from 53% in 2002 to 78% today"]

Meanwhile, support for the Turkish military has plummeted since 2007, from 85% positive ratings then to just bare majority support now (55%).

Media, such as television, radio, newspapers and magazines, also gets positive ratings from respondents. Seven-in-ten across the countries surveyed say the media is a good influence, while only about a quarter disagree. The media is especially appreciated in Africa, where a median of 88% say it is having a positive influence. This includes the highest rankings among all institutions tested in Uganda, Nigeria, Kenya and Ghana.

Middle Easterners are slightly less enamored of the media. And in Turkey, mass media is seen positively by only 32% of the public (For more on Turkish views of the media, see Turks Divided on Erdogan and the Country’s Direction published July 30, 2014).

Views of the media across countries surveyed have been relatively stable. In 2007, a median of 70% saw television, radio and newspapers as a good influence, and a median of 65% across 19 countries say the same in 2014. However, significant drops have occurred in Ukraine, Mexico and Poland since 2007.

While religious leaders are respected globally (a median of 69% say they are a good influence vs. 20% bad influence), there are regional differences. African publics are very positive towards leaders of religion, with a median of 86% saying they are a positive influence. This includes nine-in-ten or more in Tanzania, Senegal and Uganda. Asians and Latin Americans are also favorably inclined towards spiritual leaders, although opinions dip a bit in India (54% good influence) and Chile (45%).

However, in the Middle East, leaders of faith receive some of their lowest ratings in the survey. Less than half in Tunisia (33%), Jordan (34%), Turkey (37%) and the Palestinian territories (43%) see spiritual leaders as a good influence. These figures represent a sharp decline in views of religious leaders since 2007 in the Middle East.

In Lebanon, where 60% say religious leaders are a good influence, there is a religious divide. Roughly eight-in-ten Shia Muslims (79%) say spiritual leaders’ influence is a good thing for Lebanon, while 58% of Lebanese Christians and only 45% of Lebanese Sunni Muslims agree.

Argentina is the only country with a double-digit gain in ratings for religious leaders (up 26 percentage points) since 2007, and religious leaders are clearly the most respected group there (67% good influence).

[tweetable url="http://pewrsr.ch/CntryIssues2014"]In the Middle East, leaders of faith receive some of their lowest ratings in the survey.

Ratings for national governments vary greatly by country and region. Overall, a median of 59% across the countries surveyed have a positive impression of their own government, with 38% saying their influence is bad. National governments are more appreciated in Asia and Africa, but fewer in the Middle East and Latin America say the same. The lowest ratings for governments comes from publics in Poland, Argentina and Egypt.

Across all the 18 countries surveyed in both 2007 and 2014, median ratings for the national government have changed little in the last seven years.

Civil servants, which go hand in hand with national leadership, are generally seen as a positive (median of 54% see them as a good influence vs. 39% bad influence). But they get lower marks in Latin America. The lowest ratings for civil servants come from people in Ukraine, Mexico, Venezuela, Poland and Argentina.

The courts are most criticized in Latin America, the Middle East and Eastern Europe. Less than three-in-ten in Ukraine (14%), Argentina (19%), Chile (24%) and Brazil (25%) give the judiciary a positive rating.

Young More Fond of Corporations

For example, in Thailand, a country that is heavily dependent on exports for economic growth, the younger generation is 30 percentage points more likely to say corporations are having a good influence on their country, compared to those Thai age 50 or older. And in other emerging markets, including Argentina, Ukraine, Russia and Vietnam, the same pattern holds true.

Methods in Detail

About the 2014 Spring Pew Global Attitudes Survey

Results for the survey are based on face-to-face interviews conducted under the direction of Princeton Survey Research Associates International. Survey results are based on national samples. For further details on sample designs, see below.

The descriptions below show the margin of sampling error based on all interviews conducted in that country. For results based on the full sample in a given country, one can say with 95% confidence that the error attributable to sampling and other random effects is plus or minus the margin of error. In addition to sampling error, one should bear in mind that question wording and practical difficulties in conducting surveys can introduce error or bias into the findings of opinion polls.

Country: Argentina
Sample design: Multi-stage cluster sample stratified by locality size
Mode: Face-to-face adults 18 plus
Languages: Spanish
Fieldwork dates: April 17 – May 11, 2014
Sample size: 1,000
Margin of error: +/-3.9 percentage points
Representative: Adult population (excluding dispersed rural population, or 6.5% of the population)
Country: Bangladesh
Sample design: Multi-stage cluster sample stratified by administrative division and urbanity
Mode: Face-to-face adults 18 plus
Languages: Bengali
Fieldwork dates: April 14 – May 11, 2014
Sample size: 1,000
Margin of error: +/-3.8 percentage points
Representative: Adult population
Country: Brazil
Sample design: Multi-stage cluster sample stratified by region and size of municipality
Mode: Face-to-face adults 18 plus
Languages: Portuguese
Fieldwork dates: April 10 – April 30, 2014
Sample size: 1,003
Margin of error: +/-3.8 percentage points
Representative: Adult population
Country: Chile
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Spanish
Fieldwork dates: April 25 – May 5, 2014
Sample size: 1,000
Margin of error: +/-3.8 percentage points
Representative: Adult population (excluding Chiloe and other islands, or about 3% of the population)
Country: China
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Chinese (Mandarin, Fuping, Renshou, Suining, Xichuan, Hua, Shanghai, Chenzhou, Anlong, Chengdu, Yingkou, Guang’an, Zibo, Jinxi, Yantai, Feicheng, Leiyang, Yuanjiang, Daye, Beijing, Yangchun, Nanjing, Shucheng, Linxia, Yongxin, Chun’an, Xinyang, Shangyu, Baiyin, Ruichang, Xinghua and Yizhou dialects)
Fieldwork dates: April 11 – May 15, 2014
Sample size: 3,190
Margin of error: +/-3.5 percentage points
Representative: Adult population (excluding Tibet, Xinjiang, Hong Kong and Macau, or about 2% of the population). Disproportionately urban. The data were weighted to reflect the actual urbanity distribution in China.
Note: The results cited are from Horizonkey’s self-sponsored survey.
Country: Colombia
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Spanish
Fieldwork dates: April 12 – May 8, 2014
Sample size: 1,002
Margin of error: +/-3.5 percentage points
Representative: Adult population (excluding region formerly called the National Territories and the islands of San Andres and Providencia, or about 4% of the population)
Country: Egypt
Sample design: Multi-stage cluster sample stratified by governorate and urbanity
Mode: Face-to-face adults 18 plus
Languages: Arabic
Fieldwork dates: April 10 – April 29, 2014
Sample size: 1,000
Margin of error: +/-4.3 percentage points
Representative: Adult population (excluding frontier governorates, or about 2% of the population)
Country: El Salvador
Sample design: Multi-stage cluster sample stratified by department and urbanity
Mode: Face-to-face adults 18 plus
Languages: Spanish
Fieldwork dates: April 28 – May 9, 2014
Sample size: 1,010
Margin of error: +/-4.5 percentage points
Representative: Adult population
Country: Ghana
Sample design: Multi-stage cluster sample stratified by region and settlement size
Mode: Face-to-face adults 18 plus
Languages: Akan (Twi), English, Dagbani, Ewe
Fieldwork dates: May 5 – May 31, 2014
Sample size: 1,000
Margin of error: +/-3.8 percentage points
Representative: Adult population
Country: India
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Hindi, Bengali, Tamil, Telugu, Marathi, Kannada, Gujarati, Odia
Fieldwork dates: April 14 – May 1, 2014
Sample size: 2,464
Margin of error: +/-3.1 percentage points
Representative: Adult population in 15 of the 17 most populous states (Kerala and Assam were excluded) and the Union Territory of Delhi (roughly 91% of the population). Disproportionately urban. The data were weighted to reflect the actual urbanity distribution in India.
Country: Indonesia
Sample design: Multi-stage cluster sample stratified by province and urbanity
Mode: Face-to-face adults 18 plus
Languages: Bahasa Indonesian
Fieldwork dates: April 17 – May 23, 2014
Sample size: 1,000
Margin of error: +/-4.0 percentage points
Representative: Adult population (excluding Papua and remote areas or provinces with small populations, or 12% of the population)
Country: Jordan
Sample design: Multi-stage cluster sample stratified by governorate and urbanity
Mode: Face-to-face adults 18 plus
Languages: Arabic
Fieldwork dates: April 11 – April 29, 2014
Sample size: 1,000
Margin of error: +/-4.5 percentage points
Representative: Adult population
Country: Kenya
Sample design: Multi-stage cluster sample stratified by province and settlement size
Mode: Face-to-face adults 18 plus
Languages: Kiswahili, English
Fieldwork dates: April 18 – April 28, 2014
Sample size: 1,015
Margin of error: +/-4.0 percentage points
Representative: Adult population
Country: Lebanon
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Arabic
Fieldwork dates: April 11 – May 2, 2014
Sample size: 1,000
Margin of error: +/-4.1 percentage points
Representative: Adult population (excluding a small area in Beirut controlled by a militia group and a few villages in the south of Lebanon, which border Israel and are inaccessible to outsiders, or about 2% of the population)
Country: Malaysia
Sample design: Multi-stage cluster sample stratified by state and urbanity
Mode: Face-to-face adults 18 plus
Languages: Bahasa Malaysia, Mandarin Chinese, English
Fieldwork dates: April 10 – May 23, 2014
Sample size: 1,010
Margin of error: +/-3.8 percentage points
Representative: Adult population (excluding difficult to access areas in Sabah and Sarawak, or about 7% of the population)
Country: Mexico
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Spanish
Fieldwork dates: April 21 – May 2, 2014
Sample size: 1,000
Margin of error: +/-4.0 percentage points
Representative: Adult population
Country: Nicaragua
Sample design: Multi-stage cluster sample stratified by department and urbanity
Mode: Face-to-face adults 18 plus
Languages: Spanish
Fieldwork dates: April 23 – May 11, 2014
Sample size: 1,008
Margin of error: +/-4.0 percentage points
Representative: Adult population (excluding residents of gated communities and multi-story residential buildings, or less than 1% of the population)
Country: Nigeria
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: English, Hausa, Yoruba, Igbo
Fieldwork dates: April 11 – May 25, 2014
Sample size: 1,014
Margin of error: +/-4.3 percentage points
Representative: Adult population (excluding Adamawa, Borno, Cross River, Jigawa, Yobe, and some areas in Taraba, or roughly 12% of the population)
Country: Pakistan
Sample design: Multi-stage cluster sample stratified by province and urbanity
Mode: Face-to-face adults 18 plus
Languages: Urdu, Pashto, Punjabi, Saraiki, Sindhi
Fieldwork dates: April 15 – May 7, 2014
Sample size: 1,203
Margin of error: +/-4.2 percentage points
Representative: Adult population (excluding the Federally Administered Tribal Areas, Gilgit-Baltistan, Azad Jammu and Kashmir for security reasons, areas of instability in Khyber Pakhtunkhwa [formerly the North-West Frontier Province] and Baluchistan, military restricted areas and villages with less than 100 inhabitants – together, roughly 18% of the population). Disproportionately urban. The data were weighted to reflect the actual urbanity distribution in Pakistan.
Country: Palestinian territories
Sample design: Multi-stage cluster sample stratified by region and urban/rural/refugee camp population
Mode: Face-to-face adults 18 plus
Languages: Arabic
Fieldwork dates: April 15 – April 22, 2014
Sample size: 1,000
Margin of error: +/-4.4 percentage points
Representative: Adult population (excluding Bedouins who regularly change residence and some communities near Israeli settlements where military restrictions make access difficult, or roughly 5% of the population)
Country: Peru
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Spanish
Fieldwork dates: April 11 – May 2, 2014
Sample size: 1,000
Margin of error: +/-4.0 percentage points
Representative: Adult population
Country: Philippines
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Tagalog, Cebuano, Ilonggo, Ilocano, Bicolano
Fieldwork dates: May 1 – May 21, 2014
Sample size: 1,008
Margin of error: +/-4.0 percentage points
Representative: Adult population
Country: Poland
Sample design: Multi-stage cluster sample stratified by province and urbanity
Mode: Face-to-face adults 18 plus
Languages: Polish
Fieldwork dates: March 17 – April 8, 2014
Sample size: 1,010
Margin of error: +/-3.6 percentage points
Representative: Adult population
Country: Russia
Sample design: Multi-stage cluster sample stratified by Russia’s eight geographic regions, plus the cities of Moscow and St. Petersburg, and by urban-rural status
Mode: Face-to-face adults 18 plus
Languages: Russian
Fieldwork dates: April 4 – April 20, 2014
Sample size: 1,000
Margin of error: +/-3.6 percentage points
Representative: Adult population (excludes Chechen Republic, Ingush Republic and remote territories in the Far North – together, roughly 3% of the population)
Country: Senegal
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Wolof, French
Fieldwork dates: April 17 – May 2, 2014
Sample size: 1,000
Margin of error: +/-3.7 percentage points
Representative: Adult population
Country: South Africa
Sample design: Multi-stage cluster sample stratified by metropolitan area, province and urbanity
Mode: Face-to-face adults 18 plus
Languages: English, Zulu, Xhosa, South Sotho, Afrikaans, North Sotho
Fieldwork dates: May 18 – June 5, 2014
Sample size: 1,000
Margin of error: +/-3.5 percentage points
Representative: Adult population
Country: Tanzania
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Kiswahili
Fieldwork dates: April 18 – May 7, 2014
Sample size: 1,016
Margin of error: +/-4.0 percentage points
Representative: Adult population (excluding Zanzibar, or about 3% of the population)
Country: Thailand
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Thai
Fieldwork dates: April 23 – May 24, 2014
Sample size: 1,000
Margin of error: +/-3.9 percentage points
Representative: Adult population (excluding the provinces of Narathiwat, Pattani, and Yala, or about 3% of the population)
Country: Tunisia
Sample design: Multi-stage cluster sample stratified by governorate and urbanity
Mode: Face-to-face adults 18 plus
Languages: Tunisian Arabic
Fieldwork dates: April 19 – May 9, 2014
Sample size: 1,000
Margin of error: +/-4.0 percentage points
Representative: Adult population
Country: Turkey
Sample design: Multi-stage cluster sample stratified by region, urbanity and settlement size
Mode: Face-to-face adults 18 plus
Languages: Turkish
Fieldwork dates: April 11 – May 16, 2014
Sample size: 1,001
Margin of error: +/-4.5 percentage points
Representative: Adult population
Country: Uganda
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Luganda, English, Runyankole/Rukiga, Luo, Runyoro/Rutoro, Ateso, Lugbara
Fieldwork dates: April 25 – May 9, 2014
Sample size: 1,007
Margin of error: +/-3.9 percentage points
Representative: Adult population
Country: Ukraine
Sample design: Multi-stage cluster sample stratified by Ukraine’s six regions plus ten of the largest cities – Kyiv (Kiev), Kharkiv, Dnipropetrovsk, Odessa, Donetsk, Zaporizhia, Lviv, Kryvyi Rih, Lugansk, and Mikolayev – as well as three cities on the Crimean peninsula – Simferopol, Sevastopol, and Kerch
Mode: Face-to-face adults 18 plus
Languages: Russian, Ukrainian
Fieldwork dates: April 5 – April 23, 2014
Sample size: 1,659
Margin of error: +/-3.3 percentage points
Representative: Adult population (Survey includes oversamples of Crimea and of the South, East and Southeast regions. The data were weighted to reflect the actual regional distribution in Ukraine.)
Country: Venezuela
Sample design: Multi-stage cluster sample stratified by region and parish size
Mode: Face-to-face adults 18 plus
Languages: Spanish
Fieldwork dates: April 11 – May 10, 2014
Sample size: 1,000
Margin of error: +/-3.5 percentage points
Representative: Adult population (excluding remote areas, or about 4% of population)
Country: Vietnam
Sample design: Multi-stage cluster sample stratified by region and urbanity
Mode: Face-to-face adults 18 plus
Languages: Vietnamese
Fieldwork dates: April 16 – May 8, 2014
Sample size: 1,000
Margin of error: +/-4.5 percentage points
Representative: Adult population