metadata: authors: 0: author: Arampatzi,Efstratia
1: author: Burger,Martijn
2: author: Ianchovichina,Elena
3: author: Röhricht,Tina
4: author: Veenhoven,Ruut
count: Middle East and North Africa
docna: 0: docna: Unhappy development : dissatisfaction with
            life on the eve of the Arab spring
docty: Policy Research Working Paper
subtopic: Labor Markets,Educational Sciences,Employment and Unemployment,Health Care Services Industry,Rural Labor Markets
teratopic: Industry,Social Protections and Labor,Rural Development,Education
abstracts: cdata!: Despite progress in economic and social
            development in the 2000s, there was an increasing
            dissatisfaction with life among the population of many
            developing Arab countries. At the end of the decade, these
            countries ranked among the least happy economies in the
            world—a situation that fits the so-called “unhappy
            development” paradox. The paradox is defined as declining
            levels of happiness at a time of moderate-to-rapid economic
            development. This paper empirically tests the strength of
            association of a range of objective and subjective factors
            with life evaluation in the Middle East and North Africa
            region in the years immediately preceding the Arab Spring
            uprisings (2009–10). The findings suggest a significant,
            negative association between life satisfaction levels in the
            region during this period and each of the main perceived
            reasons for the 2011 uprisings—dissatisfaction with the
            standard of living, poor labor market conditions, and corruption.
repnme: repnme: Unhappy development : dissatisfaction with
            life on the eve of the Arab spring
display_title: Unhappy development :
            dissatisfaction with life on the eve of the Arab spring
listing_relative_url: /research/2015/11/25382796/unhappy-development-dissatisfaction-life-eve-arab-spring
topicv3: Labor Markets m1326488 855,Education m1327048 470,Jobs m1503931 2670,Unemployment m1504051 2747,Health m1504661 3480
publishtoextweb_dt: 2015-11-12T00:00:00Z
historic_topic: Industry,Social Protections and Labor,Rural Development,Education
no_of_pages: 42
author_keys: 0: author_key: 1210533
1: author_key: 453205
model_extractions: WPS7488 Policy Research Working Paper 7488 Unhappy Development Dissatisfaction with Life on the Eve of the Arab Spring _Efstratia Arampatzi Martijn Burger Elena Ianchovichina Tina Röhricht Ruut Veenhoven_ Middle East and North Africa Region Office of the Chief Economist November 2015
Policy Research Working Paper 7488

# **Abstract**

Despite progress in economic and social development in the 2000s, there was an increasing dissatisfaction with life among the population of many developing Arab countries. At the end of the decade, these countries ranked among the least happy economies in the world—a situation that fits the so-called “unhappy development” paradox. The paradox is defined as declining levels of happiness at a time of moderate-to-rapid economic development. This paper empirically tests the strength of association of a range of objective and subjective factors with life evaluation in the Middle East and North Africa region in the years immediately preceding the Arab Spring uprisings (2009–10). The findings suggest a significant, negative association between life satisfaction levels in the region during this period and each of the main perceived reasons for the 2011 uprisings—dissatisfaction with the standard of living, poor labor market conditions, and corruption.

This paper is a product of the Office of the Chief Economist, Middle East and North Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at eianchovichina@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Unhappy Development:**

# **Dissatisfaction with Life on the Eve of the Arab Spring**<sup></sup>

Efstratia Arampatzi,<sup></sup> Martijn Burger,<sup></sup> Elena Ianchovichina,<sup></sup> Tina Röhricht,<sup></sup> and Ruut Veenhoven<sup></sup>

## **JEL Classification: I31, Z13**

**Keywords:** developing Arab countries, Middle East and North Africa; Algeria, Egypt, Iraq, Jordan, Lebanon, Morocco, Syria, Tunisia, Palestine territories, Yemen; grievances; life satisfaction; Arab Spring; uprisings; standards of living; labor market; governance.

>  We would like to thank the participants in 13th ISQOLS (International Society for Quality-of-Life Studies) Conference in Phoenix, Arizona, the World Bank’s Arab Inequality Puzzle Workshop in Washington DC, and the European launch of the World Happiness Report at Erasmus Univeristy, Rotterdam, the Netherlands. The research was supported by funding through the World Bank’s Strategic Research Program.

>  Efstratia Arampatzi is junior researcher at the Erasmus Happiness Economics Research Organization, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, the Netherlands. E-mail: arampatzi@ese.eur.nl.

>  Martijn Burger is assistant professor at the Department of Applied Economics, Erasmus University, Rotterdam, Tinbergen Institute and academic director at the Erasmus Happiness Economics Research Organization, P.O. Box 1738, 3000 DR Rotterdam, the Netherlands, Tel: +31 (0) 10 4089579, Fax: +31 (0) 10 4089141. E-mail: mburger@ese.eur.nl. URL: http://www.mjburger.net.

>  Elena Ianchovichina is lead economist at the Chief Economist Office, Middle East and North Africa Region, the World Bank, 1818 H Street NW, Washington, DC 20433, USA, Tel: +1 202 458 8910, E-mail: eianchovichina@worldbank.org.

>  Tina Röhricht is research assistant at the Erasmus Happiness Economics Research Organization, Erasmus University Rotterdam P.O. Box 1738, 3000 DR Rotterdam, the Netherlands. E-mail: röhricht@ese.eur.nl.

>  Ruut Veenhoven is emeritus professor at the Erasmus Happiness Economics Research Organization, P.O. Box 1738, 3000 DR Rotterdam, the Netherlands and extraordinary professor at the North-West University, South Africa. E-mail: veenhoven@ese.eur.nl.
# **1. The ‘Unhappy Development’ Paradox in Developing Arab Countries**

In the 2000s, many developing countries in the Middle East and North Africa (MENA) did well according to the regularly tracked poverty statistics and human development indicators. Absolute poverty, measured at $1.25 a day, declined in all economies, except the Republic of Yemen, and was low on average. The incomes of the bottom 40 percent, measured as 2005 PPP-adjusted per capita expenditure, grew at higher rates than average expenditures in many developing Arab countries for which information was available (Ianchovichina, Mottaghi, and Devarajan 2015). The Gini inequality indexes were low by international standards and did not worsen in most MENA economies (Ianchovichina, Mottaghi, and Devarajan 2015). Importantly, the region made notable strides in reaching not only the Millennium Development Goals related to poverty and access to infrastructure services (especially drinking water and sanitation and Internet connectivity), but also in terms of reducing hunger and child and maternal mortality, and increasing school enrollment (Iqbal and Kiendrebeogo 2015).

Prior to the Arab Spring uprising, most developing MENA countries were seen as relatively stable places. Only two MENA countries—Iraq (7th) and the Republic of Yemen (15th) —made it to the top 25 of the 2010 Failed States Index<sup>1</sup> of Foreign Policy. Libya and Tunisia were ranked 111th and 118th of 177 countries, respectively, and so they appeared among the stronger and less fragile countries in the world (Goodwin 2011). With autocratic rulers in power for many years, the cracks in these countries’ models of government remained invisible to most observers, including political scientists (Gause 2011), and some even considered Islam a stabilizing force (Bromley 2014). Thus, the Arab Spring transitions of 2011 took most economists, political scientists, and policy makers by surprise (Gause 2011; Goodwin 2011; Bellin 2012; Bromley 2014).

Yet, the emergence of social discontent in the Arab countries could be detected using subjective data. Life satisfaction in many MENA countries was below the average for the group of countries at a similar level of development (figure 1a) and had dropped significantly in the years prior to the Arab Spring events (figure 1b). By the end of the 2000s, people in the developing parts of MENA, especially in the Arab Republic of Egypt, Iraq, the Syrian Arab Republic, Tunisia, and the Republic of Yemen, were among the least happy people in the world (see figure 2 and appendix A).<sup>2</sup> In Egypt, for instance, average life-evaluation levels plunged on a 0-10 scale<sup>3</sup> from 5.5 in 2007 to 4.4

> 1 The Failed States Index measures stability based on economic, political, and military indicators.

> 2 The incidence of depression was also observed to be high in MENA, according to Ferrari et al. (2013).

> 3 The two extreme ends of the range capture worst possible life (0) and best possible life (10).

2
in 2010—a deep drop in the context of improvements observed in socioeconomic statistics and growth in per capita incomes (see figure 1b).

**Figure 1a: GDP per Capita and Satisfaction with Life, 2008-10**

<!-- Start of picture text --> 8<br>7.5<br>7 ARE<br>6.5 QAT<br>SAU<br>6<br>BHR<br>JOR<br>5.5<br>DZA<br>TUN<br>IRN<br>5 DJI LBN LBY<br>EGYIRQ SYR<br>MAR<br>4.5 YEMWBG<br>4<br>3.5<br>3<br>5 6 7 8 9 10 11 12<br>Log GDP per Capita (2005 US dollars)<br>Figure 1b: Percentage Growth in GDP and Change in Satisfaction with Life (Weighted<br>Averages) in 106 Countries, 2005-10<br>1.5<br>1<br>0.5<br>ARE<br>0 WBG MAR<br>YEM<br>‐3 ‐1 1 3 5 7 9 11 13 15<br>‐0.5 LBN<br>EGY<br>JOR<br>SAU<br>‐1<br>‐1.5<br>Average Annual GDP Growth 2005‐2010<br>Average Life Evaluation<br>Change in Life Evaluation 2005‐2010<br><!-- End of picture text -->

**Figure 1b: Percentage Growth in GDP and Change in Satisfaction with Life (Weighted Averages) in 106 Countries, 2005-10**

_Sources:_ Real GDP per Capita: World Bank Development Indicators; Life Satisfaction: World Database of Happiness. _Note:_ Numbers are weighted averages for 147 countries. Abbreviations: ARE=United Arab Emirates; EGY=Egypt; JOR=Jordan; LBN=Lebanon; MAR=Morocco; SAU=Saudi Arabia; WBG=West Bank and Gaza; YEM=the Republic of Yemen.

3
<!-- Start of picture text --> ae a es ee<br>50 - - : F: co a ;<br>Pie y rol' wpt6<br>| fi ue)<br>i4<br>a<br>Pig 2<br>At - :<br>100 0 100<br>Jong<br><!-- End of picture text -->
of a shift in expectations, people may have become more frustrated with difficult-to-measure factors related to quality, such as the deterioration in the quality of public services, the ability to get good quality jobs, and institutional and environmental quality. Worsening of other subjective indicators, such as the ability to voice concerns and demand accountability and the incidence of corruption and cronyism, may have also contributed to deterioration in well-being.

Motivated by the need to understand the ‘unhappy development’ paradox in developing MENA, this paper empirically tests which factors are associated with life dissatisfaction in MENA countries in the years immediately preceding the Arab Spring uprisings (2009-10), taking into account objective and perceptions data regarding different aspects of life and society. In addition, we compare the extent to which the factors associated with life dissatisfaction are also associated with the Arab Spring social upheaval in developing MENA.

The paper adds to the literature in three ways. To our knowledge, we are the first to examine empirically the relative importance of different explanations provided for the declining life satisfaction in developing MENA in the wake of the Arab Spring. In particular, we examine several explanations or hypotheses for the fall in life satisfaction in developing MENA countries, including dissatisfaction with: (1) the political system of autocracy and limited civil freedoms, (2) the standard of living, (3) the high unemployment and poor quality jobs, and (4) corruption and crony capitalism. Second, we investigate systematically the factors behind the decline in life satisfaction by decomposing the decline into two components: a first-order effect associated with changes in the prevalence of dissatisfied individuals and a second-order effect associated with changes in the relative importance of these factors or perception domains for life satisfaction. In other words, this decomposition allows us to determine whether life satisfaction declined because a greater percentage of people became more dissatisfied with certain domain satisfactions or whether the relative importance of the domain satisfaction for subjective well-being increased. Third, we compare the factors related to unhappiness in developing MENA with the perceived reasons for the Arab Spring uprisings. We find that the main perceived reasons for the uprisings are the factors associated significantly and negatively with subjective well-being levels in developing MENA during this period. Our findings suggest that perceptions provide valuable information about public preferences and needs, which are typically not reflected in objective data (Veenhoven 2002). In other words, we make the case that both objective and subjective (or perceptions) data matter for understanding the root causes of political violence (cf. Okulicz-Kozaryn 2011).

The remainder of this paper is organized as follows. Section 2 presents the potential root causes of dissatisfaction with life in developing MENA. Section 3 discusses the concepts, methodology, and 5
data used in the empirical exploration. The results of this empirical analysis are presented in section 4. Finally, section 5 concludes with a summary of findings, a discussion of how these results link to the reasons for the Arab Spring uprisings, and a few caveats.

# **2. Root Causes of Dissatisfaction with Life in Developing MENA Countries**

A look at the universal conditions for happiness, as presented in cross-country studies focusing on life satisfaction, provides limited understanding of the root causes of dissatisfaction with life in the Arab world. To understand the factors shaping the subjective well-being in the developing Arab countries prior to the Arab Spring, we must factor in explicitly the social context in these countries during this time period.

There is no consensus on the root causes for life dissatisfaction in the Arab world on the eve of the Arab Spring. Several explanations have been put forward: (1) limited freedom and voice in predominantly autocratic states; (2) dissatisfaction with standards of living; (3) unhappiness with persistent unemployment and lack of good jobs due to the growing informality of the private sector; and (4) dissatisfaction with corruption and cronyism, which limits opportunities for those who work hard. Each of these explanations is discussed in greater detail below.

# **Autocracy**

On the eve of the Arab Spring, most Arab states were longstanding autocracies (Chekir and Diwan 2012; Bromley 2014; and Cammett and Diwan 2013). Power was concentrated in the hands of one person or a small group of elites, backed by the military, who made decisions subject to few legal restraints and mechanisms of popular control. At the same time, the public had few if any channels of safe expression of opinions and grievances and opportunities to develop strong civil society. The longstanding regimes managed to stay in power through a combination of repressive practices and a social contract, which extended benefits such as free public education and health, energy, and food subsidies, and guarantees of public employment in exchange for political support (Bellin 2004; Bromley 2014; Cammett and Diwan 2013). Cammett and Diwan (2013) refer to this social contract as an ‘autocratic bargain,’ in which the middle class was lured with ‘material benefits’ in exchange for ‘political quiescence.’ Thus, despite human development and economic progress after independence, the developing MENA countries scored low in terms of economic and social freedoms and the Freedom House ranked the region as the most repressive in the world (Freedom House 2008).

6
The extent to which people are free to make choices and voice opinions has a major impact on their happiness (Inglehart et al. 2008; Verme 2009). Democracies are, on average, happier than autocracies (Frey and Stutzer 2000), but the effect of democracy on happiness is stronger in countries with established democratic traditions (Dorn et al. 2007). Fereidouni, Najdi, and Amiri (2013) obtained no significant relationship between voice and accountability and happiness in developing MENA countries. Ott (2010) also found that the correlation between happiness and democracy is relatively weak in the MENA region. The ‘autocratic bargain’ may have weakened the direct link between happiness and limited freedom in developing MENA. Individuals who obtain ‘material benefits’ in exchange for political support may express dissatisfaction with living conditions rather than with the system responsible for the deterioration in the authoritarian bargain. They may initially voice mainly their dissatisfaction with living conditions and the factors affecting their quality of life, for instance, poor access to quality services and job market conditions.

# **Dissatisfaction with Standards of Living**

By the early 2000s, major cracks appeared in the social contract of redistribution without voice in developing MENA. After independence, natural resource rents enabled many Arab countries’ governments to finance redistributive policies without imposing a heavy tax burden on citizens. But in the 1990s and 2000s, fiscal pressures increased, reflecting disappointing growth in the 1980s and growing recurrent expenditures, especially on public wages and subsidies. Governments responded by downsizing the public sector, removing the guarantees of secure public jobs, and initiating reforms of the food and energy subsidy programs.<sup>4</sup> During this period, unemployment increased and many households noted deterioration in their standard of living.

High dependence on imported food and limited fiscal space meant that the global commodity price increases of the 2000s would transmit to domestic markets despite the presence of food subsidies (Korotayev and Zikina 2011; Ianchovichina, Loening, and Wood 2014).<sup>5</sup> For the poor, the increase in food and energy prices meant deterioration in their ability to meet basic needs.<sup>6</sup>

> 4 Some governments were more successful than others in cutting subsidies and improving targeting. Most economies made only partial reforms to their subsidy systems and reversed the reforms in response to the Arab Spring events.

> 5 However, prices for these basic needs are typically not well covered by standard inflation and poverty measures, which would explain why the Arab Spring came as a surprise for many scholars and policy makers. 6 According to Maslow (1943), in the hierarchy of individual demands, a person’s physiological needs for basics such as food, water, and shelter dominate all other needs. In other words, if these basic needs are not supplied, all other human needs are pushed into the background and the individual only seeks to satisfy his or her hunger. Individual anxiety over rising costs of food or shelter can therefore trigger unhappiness and, in some cases, riots (Lagi, Bertrand, and Bar-Yam 2011). The risk of riots is particularly high in lower-income countries where the share of food and other necessities in household expenditure is high (Arezki and Brückner 2011).

7
The global economic crisis of 2008 put additional stress on the MENA economies. In Egypt, the crisis was associated with a steep decline in real earnings growth; in Tunisia, it reinforced the upward trend in unemployment; and in Jordan, it slowed employment growth. Dissatisfaction with basic public services such as health care, housing, schools, and infrastructure also grew in the developing MENA countries, according to Gallup World Poll data, reflecting the erosion in the quality of public services.

By the end of the 2000s, this erosion in standards of living was felt not only by the poor, but also by other segments of the population, including the middle class. A gradual shift in government support to the elites became a particular concern (Cammett and Diwan 2013). People were frustrated because they could not get ahead by working hard and share in the prosperity generated by the relatively few large and successful Arab firms that were mostly state-owned or privately owned companies (OECD 2009).<sup>7</sup> Reflecting diminishing marginal utility, the widespread system of subsidies could not compensate for the erosion of living standards; food and energy subsidies mattered less for the well-being of the middle class than they did for the well-being of the poor and vulnerable (Ianchovichina, Mottaghi, and Devarajan 2015).

# **Unemployment and Low Quality Jobs**

Dissatisfaction with job market conditions was particularly strong in developing MENA in the wake of the Arab Spring. In the preceding decade, the MENA region’s average, aggregate and youth unemployment rates were the highest in the world. Without guarantees of secure public jobs, young people, who entered the labor market better prepared than their parents in terms of educational qualifications (Barro and Lee 2010; Campante and Chor 2012), were forced to queue for public sector jobs or take part-time or low-quality jobs in the informal sector (Chamlou 2013).<sup>8</sup> Employment in the informal sector offered little protection at old age and limited access to quality health care and benefits, such as paid maternity and annual leave (Angel-Urdinola and Kuddo 2011; World Bank 2014b).

The mismatch between educational attainment and economic opportunities created a gap between reality and expectations, lowering youth’s life satisfaction, amplifying perceptions of inequality and unfairness, and potentially contributing to social unrest (Campante and Chor 2012). In the literature, the negative association between happiness and unemployment is well-established and can be explained by a combination of income loss and psychic costs related to psychological

> 7 According to OECD (2009), very few large Arab firms are publicly traded companies.

> 8 The informal sector consists of firms, workers, and activities that operate outside the legal and regulatory frameworks.

8
distress and loss of identity and self-respect (Veenhoven 1989; Gallie and Russel 1998). The deterring effect of unemployment on happiness is more severe for the long-term unemployed (Clark and Oswald 1994), which is particularly high in the MENA region, and for people with limited job opportunities (Clark, Knabe, and Rätzel 2010).

# **Crony Capitalism and ‘Wasta’**

At a time when public sector employment was contracting, private sector growth was sluggish and few people could find jobs in the formal private sector (Malik and Awadallah 2013). Private sector growth was stifled by ‘cronyism’ and fears that a rise of the ‘nouveau rich’ class would challenge existing power relations.<sup>9</sup> Reforms in the 1990s were implemented in an uneven way, benefiting mainly the elites (Chekir and Diwan 2012; Rijkers et al. 2014) who dominated a range of economic sectors (Malik and Awadallah 2013).

Perceptions about corruption and crony capitalism also worsened in the wake of the Arab Spring (Cammett and Diwan 2013), as reflected in the retreat of MENA countries’ rankings on the Corruption Perceptions Index of Transparency International between 2000 and 2010. In addition, most MENA countries scored below average on various governance indicator rankings in the 2000s (for example, Kaufmann, Kraay, and Mastruzzi 2011).

Corruption and cronyism flourished in developing MENA with detrimental effects not only on aggregate economic and private sector growth, but also on people’s subjective well-being (Ott 2010). There was growing frustration with inequality of opportunity in labor markets and the increased importance of ‘wasta’ or connections with the elites in getting good quality jobs. These feelings were broadly shared and reflected perceptions of citizens that ‘wasta’ matters more than credentials for getting good jobs.

In summary, it can be argued that the growing dissatisfaction in the wake of the Arab Spring was fueled by a mix of grievances related to the standards of living, unemployment and low quality jobs, and ‘wasta’ or cronyism. The rest of the paper will test these hypotheses.

# **3. Concepts, Methodology, and Data**

The word ‘happiness’ is used in various ways (Veenhoven 2012). In the broadest sense, it is an umbrella term for all that is good. However, in the social sciences, the word ‘happiness’ is also used

> 9 The ruling elites controlled large parts of the private sector and profited from monopoly rights and cheap access to land and other resources (Cammett and Diwan 2013).

9
in a more specific way, which refers to an individual’s subjective appreciation of his or her own life. Accordingly, the concept of ‘happiness’ has been defined as ‘ _the degree to which an individual judges the overall quality of his/her own life-as-a-whole favorably’_ (Veenhoven 1984, chapter 2). This is also commonly referred to by terms such as ‘subjective well-being’ and ‘life satisfaction.’ Thus defined, happiness is something on one’s mind that can be measured using surveys. Common survey questions<sup>10</sup> read: ‘ _Taking all together, how happy would you say you are: very happy, quite happy, not very happy, not at all happy?_ ’ (a standard item in the World Value Studies) or ‘ _Please imagine a ladder, with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time?_ ’ (a standard item in the Gallup World Poll). Responses to this question from the Gallup World Poll are used in the empirical part of this paper. This question captures predominantly the cognitive component of happiness, also known as contentment.

How happy people are depends on _objective conditions_ and _subjective factors_ , including perceptions and expectations. According to Layard (2006), objective factors such as gender, age, marital and education status, financial situation, and health determine to a large extent life satisfaction, but subjective factors associated with perceptions and expectations about family relationships, work, community and friends, personal freedom, institutional quality, and personal values are also imperative to individual happiness. These domains of life reflect the most important human needs as identified by Maslow (1943). The relative importance of the objective and subjective determinants of life satisfaction vary over time and across individuals.

To analyze the roots of dissatisfaction with life in developing MENA in the wake of the Arab Spring, we used cross-sectional data from the Gallup World Poll for the years 2009-10 and a simple reduced-form life satisfaction model (see Di Tella, MacCulloch, and Oswald 2003; Arampatzi, Burger, and Veenhoven 2015):

**LS jit = Θ Individual_Perceptions jit + Σ Personal_Characteristics jit + ε j+ λ t + μ jit. (1)**

In this model, LS, the overall life satisfaction of individual _j_ in country _i_ in year _t_ , depends on a vector of **Individual_Perceptions** about social conditions and domain satisfactions of individual _j_ in country _i_ in year _t_ , a vector of objective **Personal_Characteristics** of individual _j_ in country _i_ in year _t_ , a vector ε **i** of country dummies to control for time-invariant country-specific characteristics, a vector λ **t** of month-year dummies capturing time-related shocks that are common for all countries in the developing MENA region, and μ **jit** is a residual error. We estimate model 1

> 10 See Veenhoven (2012) for a discussion of the limitations of direct questioning.

10
using weighted least squares regression (WLS) with robust standard errors and weighting observations using the sampling weights provided by the Gallup World Poll.<sup>11</sup> The annual Gallup World Poll includes at least 1,000 randomly selected respondents (adult population of 15 years and older) per country and is representative at the national level. In the Gallup World Poll, individuals report on several aspects of their life, including how satisfied they are with their life as a whole and how satisfied they are with different domains of their life. The common sample we use in this paper comprises in total 25,244 respondents from 10 developing MENA countries, including Algeria, Egypt, Iraq, Jordan, Lebanon, Morocco, Palestine, Syria, Tunisia, and the Republic of Yemen.

**Figure 3: Distribution of Life Evaluation Scores in Developing MENA (percent by decile)**

<!-- Start of picture text --> 30%<br>25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>0 1 2 3 4 5 6 7 8 9 10<br><!-- End of picture text --> _Source:_ Gallup World Poll 2013.

Life satisfaction was measured using a single question, known as the ‘Cantril Ladder’ or ‘SelfAnchoring Striving Scale’ (Cantril 1965). This question asks on which step of the ladder, with steps from 0 to 10, a person feels he or she stands at present. The higher the score on the ladder, the closer one’s life is seen to his or her ideal life. Figure 3 shows the distribution of happiness scores in the developing MENA region in the 2009-10 period. The unhappiness in the region is evidenced by the fact that 61 percent of the developing MENA population scores 5 or lower on the Cantril Ladder, while only 10 percent gives his or her life a score of 8 or higher. Within developing MENA, the degree of life satisfaction ranges by country from 4.66 in the Republic of Yemen to 6.23 in Jordan (table 1). It is worth noting that a person with high expectations is more likely to be

> 11 Following Ferrer-i-Carbonell and Frijters (2004), we treat the dependent variable as cardinal and not as ordinal.

11
dissatisfied with his life than a person with low expectations. Thus, the life satisfaction variable captures indirectly the effect of a gap between expected and real welfare.

**Table 1: Life Satisfaction in Developing MENA Countries in the Common Sample, (200910)**

|**Variable**|**Observations**|**Mean**|**SD**|**Min.**|**Max.**|
|---|---|---|---|---|---|
|Algeria|3,588|5.58|1.65|0|10|
|Egypt, Arab. Rep.|1,628|4.88|2.14|0|10|
|Jordan|691|6.23|1.81|0|10|
|Iraq|2,432|5.07|1.72|0|10|
|Lebanon|3,382|5.29|2.29|0|10|
|Morocco|3,144|4.97|1.67|0|10|
|Palestine|2,942|4.83|2.14|0|10|
|Syrian Arab Republic|2,169|4.86|2.12|0|10|
|Tunisia|2,048|5.17|1.69|0|10|
|Yemen, Rep.|3,184|4.66|2.21|0|10|

_Source:_ Gallup World Poll 2013.

Our main variables of interest relate to the domain-specific characteristics thought to have a most profound influence on life satisfaction in the wake of the Arab Spring as discussed in section 2. The Gallup World Poll does not have a question on the degree to which people are satisfied with the political system in the MENA countries. Since in autocracies people’s ability to make choices is restricted, we instead turn to the question: “ _Are you satisfied or dissatisfied with your freedom to choose what you do with your life?”_ We recognize, however, that this question also reflects how satisfied people are with their freedom to make individual choices about education, marriage, children, and employment. The answer to this question is zero for those who are satisfied and one for those who are dissatisfied with their freedom to make choices.<sup>12</sup> We control for objective measures of standards of living by including individual income (given in international dollars). We also include subjective evaluations of living standards based on the answers to the following question: “ _Are you satisfied or dissatisfied with your standard of living, all the things you can buy and do?”_ The answers to this question reflect how people value monetary and

> 12 People answering “don’t know” or who refused to answer this and other questions were omitted from the sample.

12
nonmonetary factors. The latter pertain to the quality of living conditions, including those related to the environment, local institutions, political and economic stability, infrastructure, health and education services, and community safety and cohesion. Other nonmonetary factors are related to the quality of jobs, the variety of choices available to people living in a given area, and the cultural context. Finally, the answers to this question factor in people’s expectations about the future, which may change over time, and people’s own views on what their standard of living should be given the amount of effort they spend at work. The possible answers to this question are zero if satisfied and one if dissatisfied.

To examine the effects of unemployment, underemployment, and job market conditions, we include subjective and objective variables related to employment and the education system. With regard to employment status, we distinguish between individuals who are paid employees (reference category), self-employed, underemployed, unemployed, or out of the workforce. The underemployed are respondents who are employed part-time, but who would like to work fulltime, while the unemployed respondents are not employed at all and are looking for job opportunities. Respondents who were out of the workforce included homemakers, students, and retirees. In addition, we control for whether people are employed in government positions or not (reference category is “Other”).

To reflect on job market conditions and the availability of high-quality jobs, respondents were asked: “ _Are you satisfied or dissatisfied with efforts to increase the number of quality jobs?_ ” to which they could either reply with a zero if satisfied or one if dissatisfied. The question: “ _In the city or area where you live are you satisfied or dissatisfied with the education system or the schools?”_ allows us to capture the effect on life satisfaction of service provision, in particular education services, which determine employment opportunities later in life. The answer to this question can be zero if satisfied or one if dissatisfied.

To explore the effect of corruption, cronyism, and ‘wasta’ on life satisfaction, we focus on government corruption as a proxy for perceptions of corruption. The answer to the question: “ _Is corruption widespread within government?”_ could be zero, if the level of corruption within government is limited, or one, if government corruption is widespread. When information regarding corruption in government was not available, the question “ _Is corruption widespread within business?”_ was used (cf. Helliwell, Layard, and Sachs 2015). In addition, we reflect the extent to which cronyism and inequities affect people’s life satisfaction by incorporating people’s opinions on whether working hard pays off. The answers to the question: “ _Can people in this country get ahead by working hard or not?”_ are zero if satisfied and one if dissatisfied.

13
Finally, we control for personal characteristics (demographic characteristics) that may confound the relationship between the designated factors and life satisfaction in developing MENA. These personal characteristics are related to gender, age, marital status and household composition, education level, migration status, and religion. An overview of all variables included in the analysis (including descriptive statistics) and a correlation matrix are provided in appendixes B1, B2, and B3.

# **4. Empirical Results**

This section discusses the results from the baseline and alternative specifications, the results’ sensitivity to changes in variable specifications and data aggregations, as well as endogeneity bias issues.

# **Baseline and Alternative Specifications: Ordinary Least Squares Results**

Table 2 reports results from different specifications using the Cantril Ladder as dependent variable. In the first specification, we have only control variables for personal characteristics. In specifications 2 to 6, we separately include each of the subjective domain satisfaction variables associated with dissatisfaction in developing MENA, along with related objective factors. In specification 7, all subjective and objective variables are included simultaneously. The final specification in table 2 (model 8) is a replication of model 7 using a reduced sample of countries that experienced uprisings related to the Arab Spring. All the specifications include country and time dummies. The country dummies capture time-invariant, country-specific factors, such as the size of the country, culture, language, distance to markets, and structural features of the political and economic environment. The time dummies control for exogenous factors that changed over the period of interest, controlling herewith for contagion effects in the aftermath of the global financial crisis.

In line with the empirical literature on happiness, education and marriage are positively associated with life satisfaction in developing MENA. Against the prevailing perception in the West, Arab women are on average happier than men. Focusing on the main sources of discontent in the wake of the Arab Spring (models 2 to 7), the main findings can be summarized as follows. First, although dissatisfaction with freedom to choose what you do with your life has a negative and significant effect on life satisfaction (table 2, model 2), this effect disappears after controlling for other perceptions (table 2, model 7). This finding supports the view that the social contract has weakened the direct link between authoritarianism (for example, lack of freedom) and life satisfaction. So it is the effect of the authoritarian political system on economic well-being and other domains of life, 14
rather than freedom per se, that initiated unrest in developing MENA countries. It is therefore not surprising that dissatisfaction with standards of living has the largest and strongly significant negative effect on life satisfaction (table 2, models 3 and 7). On average, the life satisfaction score of dissatisfied respondents is 1.24 points lower than the life satisfaction score of respondents who are satisfied with their living standards in the fully specified model in table 2, model 7.

Second, poor job market conditions are significantly and negatively related to dissatisfaction in developing MENA countries—a result that retains significance even when we include all other subjective variables (table 2, models 4 and 7). The unemployed and underemployed report life satisfaction scores that are, respectively, 0.34 and 0.11 points lower than people in paid employment. Lack of quality jobs is another reason for the discontent and remains a significant factor even after we control for employment status. On average, respondents who indicate dissatisfaction with the availability of high quality jobs report 0.15 point lower life satisfaction than those who are satisfied with job quality (table 2, model 7). Not surprisingly, people working for the government (considered to be the best kind of jobs in MENA) are, on average, significantly happier than people working in the private sector.

Third, we find that dissatisfaction with the education system is associated with life dissatisfaction in developing MENA. Respondents who are dissatisfied with the educational system report 0.17 point lower satisfaction with life than those who are satisfied with the education system (table 2, models 4 and 7).

Fourth, perceptions of inequality of opportunities ( or ‘wasta’), corruption, and crony capitalism are significantly and negatively associated with life satisfaction in developing MENA (table 2, model 5 to 7). Respondents who think that people cannot get ahead by working hard report, on average, a 0.22 point lower life satisfaction score than those who are satisfied with this dimension of life satisfaction. Respondents who believe that corruption is widespread in the government are on average 0.27 point less satisfied with life, although this effect is reduced controlling for other perceptions (table 2 , models 5 and 7). Thus, in MENA, the governance problem is perceived to affect life satisfaction not so much through corruption in government, but through practices that affect all aspects of life and prevent people (and those working in the private sector, more generally) from succeeding even when they make great efforts to excel and do a good job. This result is consistent with the findings in Rijkers, Freund, and Nucifora (2014) and World Bank (2014a).

15
**Table 2: Determinants of Life Satisfaction in MENA: Ordinary Least Squares Estimates**

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|VARIABLES|Model 1|Model 2|Model 3|Model 4|Model 5|Model 6|Model 7|Model 8|
||DEV<br>MENA|DEV<br>MENA|DEV<br>MENA|DEV<br>MENA|DEV<br>MENA|DEV<br>MENA|DEV<br>MENA|Arab<br>Spring|
|Dissatisfied with freedom to choose life: Yes||-0.351***|||||-0.033|-0.019|
|||(0.030)|||||(0.031)|(0.053)|
|Dissatisfied with standard of living: Yes|||-1.333***||||<br>-1.238***|<br>-1.213***|
||||(0.029)||||(0.030)|(0.053)|
|Income (1,000’s)|||<br>0.023***|0.029***|||<br>0.023***|<br>0.025***|
||||(0.002)|(0.002)|||(0.002)|(0.003)|
|Dissatisfied with efforts to increase high quality||||-0.361***|||-0.154***|-0.139***|
|<br>jobs: Yes||||(0.031)|||(0.032)|(0.053)|
|Dissatisfied with the educational system or the||||-0.340***|||-0.166***|-0.158***|
|schools: Yes||||(0.030)|||(0.029)|(0.051)|
|_(Reference group: Full-time Employed)_|||||||||
|Self-employed||||0.077|||0.041|-0.024|
|||||(0.064)|||(0.061)|(0.100)|
|Unemployed||||-0.534***|||-0.335***|-0.475***|
|||||(0.082)|||(0.079)|(0.145)|
|Out of workforce||||<br>0.003|||<br>-0.019|<br>-0.028|
|||||(0.049)|||(0.047)|(0.076)|
|Underemployed||||<br>-0.267***|||<br>-0.114|<br>-0.242*|
|||||(0.082)|||(0.080)|(0.133)|
|_(Reference group: Other)_|||||||||
|<br>Working for the government||||0.245***|||0.190***|0.309***|
|||||(0.055)|||(0.052)|(0.084)|
|Undetermined||||-0.011|||-0.019|-0.280***|
|||||(0.051)|||(0.049)|(0.095)|
|Corruption widespread within government: Yes|||||-0.277***||<br>-0.077**|<br>-0.056|
||||||(0.036)||(0.035)|(0.054)|
|People cannot get ahead by working hard: Yes||||||-0.496***|<br>-0.223***|<br>-0.210***|
|||||||(0.041)|(0.039)|(0.080)|
|_(Reference group: Muslim)_|||||||||
|Not Muslim/Other religion|0.269***|0.237***|0.202***|0.168**|0.275***|0.239***|0.171**|0.176|
||(0.075)|(0.075)|(0.069)|(0.074)|(0.075)|(0.074)|(0.068)|(0.152)|

16
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|_(Reference group: Completed elementary education_|_or less)_||||||||
|Completed 9-15 years of education|0.452***|0.438***|0.295***|0.356***|0.448***|0.447***|0.282***|0.393***|
||(0.033)|(0.033)|(0.031)|(0.033)|(0.033)|(0.033)|(0.031)|(0.051)|
|Completed four years of education beyond high|0.917***|0.894***|0.544***|0.672***|0.918***|0.902***|0.538***|0.533***|
|school and/or 4-year college degree.|(0.053)|(0.053)|(0.050)|(0.054)|(0.053)|(0.052)|(0.051)|(0.093)|
|_(Reference group: Not a migrant)_|||||||||
|Migrant|-0.145|-0.147|-0.264***|-0.208**|-0.142|-0.156|-0.257***|-0.729***|
||(0.102)|(0.102)|(0.097)|(0.101)|(0.102)|(0.101)|(0.096)|(0.182)|
|Female|0.221***|0.224***|0.156***|0.203***|0.216***|0.209***|0.138***|0.236***|
||(0.029)|(0.029)|(0.027)|(0.031)|(0.029)|(0.029)|(0.029)|(0.052)|
|Age|-0.040***|-0.038***|-0.029***|-0.038***|-0.039***|-0.039***|-0.028***|-0.022**|
||(0.006)|(0.006)|(0.006)|(0.006)|(0.006)|(0.006)|(0.006)|(0.009)|
|Age ^2|0.000***|0.000***|0.000***|0.000***|0.000***|0.000***|0.000***|0.000**|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|_(Reference group: Married with children)_|||||||||
|Married without children|0.092*|0.091*|0.037|0.081*|0.098**|0.088*|0.044|0.015|
||(0.047)|(0.047)|(0.044)|(0.046)|(0.047)|(0.047)|(0.043)|(0.073)|
|Single with children|-0.140***|-0.122**|-0.101**|-0.088*|-0.136***|-0.145***|-0.075|0.053|
||(0.050)|(0.050)|(0.047)|(0.049)|(0.050)|(0.050)|(0.047)|(0.079)|
|Single without children|-0.086*|-0.081|-0.102**|-0.067|-0.079|-0.088*|-0.077|-0.013|
||(0.050)|(0.050)|(0.047)|(0.049)|(0.050)|(0.050)|(0.047)|(0.080)|
|Separated/Divorced/Widow with children|<br>-0.125|<br>-0.098|<br>-0.028|<br>-0.085|<br>-0.124|<br>-0.108|<br>-0.003|<br>0.120|
||(0.083)|(0.082)|(0.077)|(0.081)|(0.083)|(0.082)|(0.076)|(0.119)|
|Separated/Divorced/Widow without children|<br>-0.404***|<br>-0.406***|<br>-0.265***|<br>-0.337***|<br>-0.390***|<br>-0.398***|<br>-0.251***|<br>-0.321**|
||(0.099)|(0.099)|(0.091)|(0.095)|(0.099)|(0.098)|(0.090)|(0.148)|
|_(Reference group: 1 person older than 15 in househ_|<br>_old)_||||||||
|2 people older than 15 in household|0.018|0.007|0.005|0.008|0.022|0.021|0.010|-0.024|
||(0.086)|(0.086)|(0.084)|(0.084)|(0.086)|(0.086)|(0.084)|(0.112)|
|More than 2 people older than 15 in household|0.030|0.008|-0.033|-0.031|0.030|0.030|-0.030|0.003|
||(0.081)|(0.082)|(0.080)|(0.080)|(0.081)|(0.081)|(0.079)|(0.107)|
|Country fixed effects|YES|YES|YES|YES|YES|YES|YES|YES|
|Month and Year of Interview|YES|YES|YES|YES|YES|YES|YES|YES|
|Constant|5.560***|5.686***|5.708***|5.747***|5.768***|5.628***|5.824***|5.588***|
||(0.172)|(0.173)|(0.163)|(0.178)|(0.173)|(0.172)|(0.173)|(0.260)|
|Observations|25,244|25,244|25,244|25,244|25,244|25,244|25,244|9,065|
|R-squared|0.071|0.078|0.197|0.121|0.074|0.079|0.206|0.192|

Note: i. Robust standard errors in parentheses; ***p<0.01; **p<0.05; *p<0.10; ii. Developing MENA includes Algeria, Egypt, Iraq, Jordan, Lebanon, Morocco, Palestine, Syria, Tunisia, and the Republic of Yemen. iii. Employment status includes an additional category (2009) which captures individuals other than employed.

17
Our ordinary least squares (OLS) results largely hold when controlling for interview dates, mood, health (appendix C1), examining heterogeneity with the MENA region (appendix C2), and using alternative variable specifications (appendix C3). Only when we add mood to our OLS baseline regression (model 7), the coefficients for dissatisfaction with availability of high quality jobs and dissatisfaction with the educational system are reduced and become statistically insignificant. Finally, model 8 replicates model 7 with a reduced sample of Arab Spring countries in which all coefficients behave similarly. Therefore, the conclusions based on the full specification for the whole sample of developing MENA countries (table 2, model 7) hold for the reduced sample of Arab Spring countries (table 2, model 8).

# **Dealing with Reverse Causality: Lewbel IV Estimator**

Our analysis possibly suffers from endogeneity bias. Reverse causality may be a particular problem since life evaluation and domain satisfaction are often jointly determined. Although the usage of conventional instrumental variable (IV) methods would be preferred in a cross-section setting, finding credible instruments is difficult; thus we made use of the Lewbel IV estimator to account for reverse causality. Conventional IVs have to satisfy the following restrictions: the instrument has to be correlated with the independent variables and has to be uncorrelated with the dependent variable and the error term. In our case, a valid instrument should be correlated with the independent variables in our regression, the life domain perceptions, but not with life satisfaction. Given the general unavailability of good instruments with this property, we resort to the implementation of an instrumental variable estimation using heteroskedasticity-based instruments for cross-sectional data, suggested by Lewbel (2012). The Lewbel IV estimator uses internally generated instruments comparable to difference Generalized Method of Moments (GMM) and system GMM in a panel data setting to isolate the effect of perceptions on life satisfaction. According to Lewbel (2012), in the absence of conventional IVs, a vector of exogenous variables _Z_ equal to _X_ or a subset of _X_ can be used to generate external instruments [Z- E(Z)]ε, given that there is some heteroskedasticity in the standard errors ε, and

# **E(Xε)=0, and cov(Z,ε)≠0.**

# **(2)**

The validity of these assumptions for our data can be questioned, so we first examine whether the Lewbel requirements are met for regression model (1). First, we test for the presence of heteroskedatisticity. Following Lewbel (2012), we performed a Breusch and Pagan Lagrange Multiplier Test to test for heteroskedasticity. The results show that the test statistic is significantly different from zero in all cases, indicating that there is enough variance in our data to avoid weak instruments. Second, before estimating the second stage of the regressions using the generated 18
instruments, we carefully consider the choice of Z. As indicated by Lewbel (2012), the vector of exogenous variables Z can be a set or subset of X and therefore the obtained estimates could be largely dependent on the specific choice of X’s. Although in general the choice of Z can be random, subject to conditions 2 above, we opted to follow a different strategy to select our instruments. Our strategy for choosing Z is based on the correlation matrix of the generated instruments. The subset of X had to satisfy two basic conditions: (i) it had to be uncorrelated with the dependent variable Y and (ii) it had to be statistically correlated with X in the first place. The generated instruments that did not meet these conditions were excluded from the second-stage regression. After testing whether the conditions were satisfied, we chose a set of instruments and estimated the model using generalized method of moments (GMM).

Table 3 provides a replication of table 2 using the Lewbel IV estimator. Several results stand out. First, dissatisfaction with freedom to choose life is not significant in model 10 or in the full specification in model 15, showing that freedom does not explain variation in life satisfaction in developing MENA in the wake of the Arab Spring. Second, in line with the OLS results, dissatisfaction with standards of living, income, and job status remain robust in sign and highly significant predictors across all specifications (models 11, 12, 15, and 16). Third, perceived poor job conditions, reflected in dissatisfaction with the efforts of the government to improve the number of high quality jobs and the educational system, do not have a significant effect on life satisfaction (models 15 and 16). It is highly likely that these domains are jointly determined or are partly reflected by satisfaction with standards of living. Fourth, the effect of cronyism and ‘wasta’ on satisfaction with life remains significant, but the effect of widespread corruption is no longer significant (models 15 and 16). This result supports our initial finding that people are affected not so much by government corruption, but by cronyism and ‘wasta,’ which make it difficult for people to succeed even when working hard.

# **Drivers of Life Satisfaction Changes on the Eve of the Arab Spring**

Perceptions about living standards, job market conditions, and cronyism have had an important effect on life satisfaction in MENA. This section explores the degree to which each of these factors has contributed to the change in life satisfaction in the period 2009-10. We decompose the change in life satisfaction into the sum of all effects attributed to changes in the incidence of dissatisfaction with each of the domains included in model 1 and another sum of effects, reflecting the change in the importance of each of these domains for people’s life satisfaction between 2009 and 2010.

19
# **Table 3: Determinants of Life Satisfaction in MENA: Lewbel Estimates**

||(10)|(11)|(12)|(13)|(14)|(15)|(16)|
|---|---|---|---|---|---|---|---|
|VARIABLES|Model 10<br>DEV<br>MENA|Model 11<br>DEV<br>MENA|Model 12<br>DEV<br>MENA|Model 13<br>DEV<br>MENA|Model 14<br>DEV<br>MENA|Model 15<br>DEV<br>MENA|Model 1<br>Arab<br>Spring|
|Dissatisfaction with freedom to choose life|-0.243|||||-0.011|0.069|
||(0.340)|||||(0.789)|(0.923)|
|Dissatisfied with standard of living: Yes||-1.299***||||<br>-1.181***|<br> <br>-1.288***|
|||(0.100)||||(0.126)|(0.186)|
|Income (1,000’s)||0.024***|0.030***|||0.023***|0.026***|
|||(0.002)|(0.002)|||(0.002)|(0.003)|
|Dissatisfied with efforts to increase high quality|||<br>-0.353***|||<br>-0.085|<br>-0.218|
|jobs: Yes|||(0.092)|||(0.262)|(0.333)|
|Dissatisfied with the educational system or the|||-0.118|||-0.076|0.515|
|schools: Yes|||(0.245)|||(0.245)|(0.524)|
|_(Reference group: Full-time Employed)_||||||||
|Self-employed|||0.079|||0.050|-0.037|
||||(0.064)|||(0.061)|(0.105)|
|Unemployed|||<br>-0.539***|||<br>-0.353***|<br>-0.504***|
||||(0.083)|||(0.086)|(0.163)|
|Out of workforce|||0.012|||-0.021|-0.038|
||||(0.049)|||(0.050)|(0.078)|
|Underemployed|||<br>-0.287***|||<br>-0.126|<br>-0.251*|
||||(0.084)|||(0.082)|(0.135)|
|_(Reference group: Other)_||||||||
|Working for the government|||0.233***|||0.187***|0.487***|
||||(0.055)|||(0.054)|(0.134)|
|Corruption widespread within government: Yes||||-0.367***||-0.188|-0.216|
|||||(0.128)||(0.181)|(0.247)|
|People cannot get ahead by working hard: Yes|||||-0.589***|<br>-0.324**|<br>-0.512*|
||||||(0.134)|(0.154)|(0.269)|
|_(Reference group: Muslim)_||||||||
|<br>Not Muslim/Other religion|0.245***|0.180***|0.165**|0.277***|0.233***|0.175*|0.238|
||(0.081)|(0.069)|(0.076)|(0.075)|(0.074)|(0.094)|(0.169)|
|_(Reference group: Completed elementary education or less_|<br>_)_|||||||
|Completed 9-15 years of education|0.443***|0.305***|0.360***|0.447***|0.445***|0.280***|0.368***|
||(0.035)|(0.032)|(0.033)|(0.033)|(0.033)|(0.037)|(0.062)|

20
||(10)|(11)|(12)|(13)|(14)|(15)|(16)|
|---|---|---|---|---|---|---|---|
|Completed four years of education beyond high<br>school and/or 4-year college degree.|0.901***<br>(0.057)|0.569***<br>(0.050)|0.679***<br>(0.054)|0.918***<br>(0.053)|0.899***<br>(0.053)|0.539***<br>(0.068)|0.486***<br>(0.136)|
|_(Reference group: Not a migrant)_||||||||
|Migrant|-0.141<br>(0.102)|-0.200**<br>(0.098)|-0.184*<br>(0.102)|-0.142<br>(0.102)|-0.155<br>(0.101)|-0.272***<br>(0.096)|-0.718***<br>(0.188)|
|Female|0.223***<br>(0.029)|0.157***<br>(0.027)|0.203***<br>(0.031)|0.215***<br>(0.029)|0.206***<br>(0.029)|0.140***<br>(0.038)|0.226***<br>(0.072)|
|Age<br>Age ^2|-0.039***<br>(0.006)<br>0.000***|-0.029***<br>(0.006)<br>0.000***|-0.038***<br>(0.006)<br>0.000***|-0.039***<br>(0.006)<br>0.000***|-0.038***<br>(0.006)<br>0.000***|-0.029***<br>(0.006)<br>0.000***|<br>-0.022**<br>(0.009)<br>0.000**|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|_(Reference group: Married with children)_||||||||
|Married without children|0.091*|0.038|0.083*|0.100**|0.087*|0.047|0.036|
||(0.047)|(0.044)|(0.046)|(0.047)|(0.047)|(0.044)|(0.076)|
|Single with children|-0.125**|-0.096**|-0.090*|-0.134***|-0.147***|-0.081|0.066|
||(0.053)|(0.047)|(0.049)|(0.050)|(0.050)|(0.057)|(0.096)|
|Single without children|-0.081|-0.095**|-0.067|-0.076|-0.089*|-0.072|-0.015|
||(0.050)|(0.047)|(0.049)|(0.050)|(0.050)|(0.047)|(0.082)|
|Separated/Divorced/Widow with children|-0.106|-0.032|-0.100|-0.123|-0.105|-0.011|0.111|
||(0.086)|(0.076)|(0.082)|(0.083)|(0.082)|(0.089)|(0.124)|
|Separated/Divorced/Widow without children|-0.403***|-0.273***|-0.343***|-0.385***|-0.399***|-0.252***|<br>-0.290*|
||(0.099)|(0.091)|(0.095)|(0.099)|(0.098)|(0.093)|(0.153)|
|_(Reference group: 1 person older than 15 in house_|_hold)_|||||||
|2 people older than 15 in household|0.010|0.017|0.007|0.023|0.024|0.010|-0.037|
||(0.087)|(0.084)|(0.085)|(0.086)|(0.086)|(0.089)|(0.125)|
|More than 2 people older than 15 in household|0.015|-0.022|-0.032|0.030|0.030|-0.032|-0.018|
||(0.085)|(0.080)|(0.081)|(0.081)|(0.081)|(0.093)|(0.135)|
|Constant|5.159***|5.452***|5.471***|5.364***|5.116***|5.570***|5.446***|
||(0.213)|(0.159)|(0.182)|(0.196)|(0.168)|(0.198)|(0.254)|
|Observations|25,244|25,244|25,244|25,244|25,244|25,244|9,065|
|R-squared<br>**Statistics**|0.077|0.193|0.117|0.074|0.079|0.204|0.076|
|Underidentification test: P-value|83.04|1105.78|194.93|503.81|454.68|29.508|23.872|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|(0.013)|(0.475)|
|Cragg-Donald Wald F statistic|42.14|563.35|31.23|729.53|425.07|1.826|1.533|
|Stock-Yogo VC 10%|10.27|10.27|10.89|19.53|10.83|NA|NA|
|Hansen statistic|4.25|4.63|5.13|0.133|0.924|8.327|7.516|
||(0.234)|(0.200)|(0.953)|(0.715)|(0.921)|(0.871)|(0.873)|

21
The first sum is the first-order or direct effect. It reflects the contribution attributed to the changes in the percentage of people dissatisfied with domains X in period 2 relative to period 1. If x2 > x1, a higher share of the population has become dissatisfied with certain aspects of individual or social life. The second-order effect shows the part of the negative association attributed to changes in the size of the effect of the obtained coefficients, implying a change in the relative importance of that factor to life satisfaction (LS). In other words, the indirect effect shows evidence that perceptions have changed, making individuals less tolerant of certain social conditions, for instance, cronyism and ‘wasta.’

**Table 4: Decomposition of the Change in Life Satisfaction between 2009 and 2010 (Based on Lewbel Estimates of Model (1))**

||Developing<br>MENA<br>First Order Effect|<br>Developing<br>MENA<br>Second Order<br>Effect|Arab Spring<br>Countries<br>First Order Effect|Arab Spring<br>Counties<br>Second Order<br>Effect|
|---|---|---|---|---|
|Dissatisfaction with standards of<br>living|-0.031|0.037|-0.084|0.005|
|People cannot get ahead by<br>working hard (Yes)|0.005|0.038|NS|NS|
|Dissatisfaction with efforts of the<br>government to increase high<br>quality jobs|-0.012|0.021|-0.030|-0.060|
|Dissatisfaction with freedom to<br>choose life|-0.014|-0.074|NS|NS|
|Corruption widespread within<br>government/business (Yes)|-0.008|-0.088|NS|NS|
|Unemployed|0.000|0.025|-0.012|0.004|
|Working for the government|NS|NS|0.020|0.043|
|Income (1,000’s)|-0.015|0.010|-0.025|-0.077|

Notes: (i) Developing MENA includes Algeria, Egypt, Iraq, Jordan (only available for 2009), Lebanon, Morocco, Palestine, Syria, Tunisia, and the Republic of Yemen. (ii) Arab Spring Countries include Egypt, Libya, Syria and the Republic of Yemen. (iii) We only present the coefficients that were significant at least for one out of two years. (iv) The coefficients that are not significant are marked as NS. (v) The full table with results can be found in the appendix.

Table 4 shows the decomposition of change in LS into the contributions of direct and indirect effects of domain satisfactions between 2009 and 2010. A more detailed table of this decomposition of effects is provided in appendix D1. In appendix D2, we also provide the results estimated with ordinary least squares. In developing MENA, the largest negative contribution to dissatisfaction with life given by the first-order effects is attributed to the increased share of individuals dissatisfied with their standard of living (-0.031) and decrease in reported income (- 0.015). Similar findings are observed for the Arab Spring countries; in this case, the coefficients are -0.084 and -0.025, respectively. The size of the effects of corruption and limited freedom on life 22
Fighting corruption was mentioned as the most important reason for the Arab Spring by 64.3 percent of respondents, followed by betterment of the economic situation (63.4 percent) and social and economic justice (57.2 percent). These findings are in line with a poll by Zogby in 2005, in which respondents in developing MENA countries indicated that the lack of employment opportunities, corruption, health care, and schooling were seen as the most pertinent problems in developing MENA countries (Zogby 2005). Strikingly, civil and political freedom (42.4 percent) only comes in fourth place and is, hence, neither found associated with dissatisfaction in developing MENA nor regarded as one of the most important factors related to the uprisings. Likewise, relations with the West (7.5 percent) and Israel (14.6 percent) as well as rule of law (15.7 percent) and dignity (28.8 percent) were less often mentioned as important reasons for the Arab Spring, and were not found to be an important determinant of dissatisfaction with life in developing MENA. Hence, standards of living, labor market conditions, and ‘wasta’ are not only strongly related to dissatisfaction with life prior to the Arab Spring, but also mentioned as the main reasons for the Arab Spring uprisings.

In sum, it can be concluded that the Arab Spring uprisings in developing MENA countries were preceded by a decline in life satisfaction from already low happiness levels, despite economic and human development progress in the prior two decades. In many developing MENA countries, the so-called “unhappy development” paradox was accompanied by social discontent driven by poor or worsening standards of living, labor market conditions, and crony capitalism. In this light, our study highlights that not only objective conditions count, but also the subjective awareness of shortcomings in these objective conditions. The rising awareness of social ills is partly due to the modernization process in which society is seen to be less of a moral order given by God, and in which an increasing number of educated people call for meritocracy rather than autocracy.

Dissatisfaction alone does not bring political action, which typically arises only in combination with perceived chances for change (Klandermans 1997). This paper does not explore the question why some developing MENA countries experienced political violence and fall of regimes, whereas in other developing MENA countries the protests remained rather limited. This question should be addressed in future research.

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28
# **Appendixes Appendix A: Average Life Satisfaction (ALS) across Countries, 2006-12**

|Rank|Country|ALS|Rank|Country|ALS|Rank|Country|ALS|
|---|---|---|---|---|---|---|---|---|
|1|Denmark|7.80|54|Poland|5.79|107|China|4.84|
|2|Switzerland|7.59|55|Sint Maarten|5.79|108|Djibouti|4.84|
|3|Norway|7.58|56|El Salvador|5.78|109|Zambia|4.81|
|4|Netherlands|7.51|57|Bolivia|5.71|110|India|4.79|
|5|Finland|7.50|58|Croatia|5.65|111|Bangladesh|4.78|
|6|Canada|7.47|59|Kazakhstan|5.64|112|Iraq|4.78|
|7|Sweden|7.41|60|Lithuania|5.59|113|Mozambique|4.76|
|8<br>|Iceland<br>|7.36<br>|61<br>|Jordan<br>|5.57<br>|114<br>|Mongolia<br>|4.72<br>|
|9|Australia|7.32|62|Belarus|5.55|115|Serbia|4.72|
|10|New Zealand|7.31|63|Ecuador|5.55|116|Angola|4.68|
|11|Austria|7.30|64|Paraguay|5.50|117|Azerbaijan|4.64|
|12|Costa Rica|7.25|65|Mauritius|5.48|118|Mauritania|4.58|
|13|Israel|7.22|66|Moldova|5.47|119|Palestine|4.58|
|14|United States|7.19|67|Hong Kong SAR, China|5.45|120|Tajikistan|4.55|
|15|Ireland|7.18|68|Uzbekistan|5.45|121|Egypt, Arab Rep.|4.53|
|16|Belgium|7.08|69|Vietnam|5.45|122|Macedonia, FYR|4.53|
|17|Luxembourg|7.04|70|Bahrain|5.43|123|Armenia|4.42|
|18|United Arab Emirates|7.04|71|Peru|5.43|124|Botswana|4.42|
|19|Panama|6.92|72|Algeria|5.42|125|Malawi|4.42|
|20|Mexico|6.91|73|Cuba|5.42|126|Nepal|4.42|
|21|United Kingdom|6.89|74|Estonia|5.37|127|Sudan|4.42|
|22|Venezuela, RB|6.89|75|Libya|5.37|128|Uganda|4.39|
|23|Oman|6.85|76|Albania|5.36|129|Congo, Dem. Rep.|4.38|
|24|Brazil|6.80|77|Kosovo|5.36|130|Cameroon|4.36|
|25|France|6.75|78|Russian Federation|5.35|131|Syrian Arab Republic|4.32|
|26|Germany|6.64|79|Honduras|5.34|132|Senegal|4.31|
|27|Spain|6.61|80|Turkey|5.26|133|Yemen, Rep.|4.27|
|28|Puerto Rico|6.59|81|Portugal|5.25|134|Kenya|4.26|
|29|Qatar|6.58|82|Indonesia|5.23|135|Sri Lanka|4.25|
|30|Saudi Arabia|6.58|83|Nicaragua|5.20|136|Côte d'Ivoire|4.20|
|31|Singapore|6.55|84|Montenegro|5.18|137|Madagascar|4.14|
|32|Kuwait|6.48|85|Romania|5.15|138|Mali|4.14|
|33|Cyprus|6.46|86|Pakistan|5.14|139|Niger|4.14|
|34|<br>Belize|6.45|87|South Africa|5.09|140|<br>Haiti|4.13|
|35|Argentina|6.35|88|Ukraine|5.08|141|Congo, Rep.|4.12|
|36|Czech Republic|6.35|89|Dominican Republic|5.05|142|Zimbabwe|4.12|
|37|Trinidad and Tobago|6.35|90|Nigeria|5.04|143|Gabon|4.11|
|38|Italy|6.33|91|Lao PDR|5.01|144|Afghanistan|4.09|
|39|Suriname|6.27|92|Lebanon|4.98|145|Burkina Faso|4.08|
|40|Colombia|6.26|93|Tunisia|4.98|146|Cambodia|4.07|
|41|Chile|6.25|94|Iran, Islamic Rep.|4.91|147|Liberia|4.04|
|42|Guatemala|6.14|95|Hungary|4.90|148|Rwanda|4.03|
|43|Uruguay|6.07|96|<br>Kyrgyz Republic|4.90|149|Chad|4.00|
|44|Japan|6.06|97|Lesotho|4.90|150|Guinea|4.00|
|45|<br>Malta|6.02|98|Ghana|4.89|151|Georgia|3.99|
|46|Thailand|6.02|99|Myanmar|4.89|152|<br>Bulgaria|3.95|
|47|Guinea-Bissau|5.99|100|Namibia|4.89|153|Central African Rep|3.87|
|48|Slovak Republic|5.98|101|Philippines|4.89|154|Tanzania|3.87|
|49|<br>Turkmenistan|5.94|102|<br>Somalia|4.89|155|Sierra Leone|3.77|
|50|Korea, Rep.|5.89|103|Bosnia and Herzegovina|4.87|156|Comoros|3.74|
|51|Greece|5.83|104|Latvia|4.87|157|Burundi|3.69|
|52|Malaysia|5.83|105|Morocco|4.87|158|Benin|3.51|
|53|Jamaica|5.81|106|Swaziland|4.87|159|Togo|2.98|

Note: Developing MENA countries are highlighted 29
# **Appendix B1: Description of Variables**

|**Category: Independent**<br>**perception variables**|**Variable code**|**Exact question**|**Answer categories**|
|---|---|---|---|
|Satisfaction with Standard of<br>Living|Wp30|Are you satisfied or dissatisfied<br>with your standard of living, all the<br>things you can buy and do?|1 Yes<br>2 No|
|Satisfaction with Standard of|Wp40|Have there been times in the past|1 Yes|
|Living||twelve months when you did not|2 No|
|(Index construction)||have enough money to buy food<br>that you or your family needed?||
|Satisfaction with Standard of|Wp43|Have there been times in the past|1 Yes|
|Living||twelve months when you did not|2 No|
|<br>(Index construction)||<br>have enough money to provide<br>adequate shelter or housing for<br>you and your family?||
|Satisfaction with Standard of<br>Living|Index_fs|<br>Construction of variable wp40 and<br>wp43|Not applicable|
|(Alternative specification)||||
|Satisfaction with freedom TO<br>CHOOSE LIFE|Wp134|Are you satisfied or dissatisfied<br>with your freedom to choose what<br>you do with your life?|1 Yes<br>2 No|
|Satisfaction with civil freedom|Wp143|<br>Do you have confidence in the|1 Yes|
|(Alternative specification)||Quality and Integrity of the<br>Media?|2 No|
|Perceptions about Corruption|Wp145|Is corruption widespread within<br>business?|1 Yes<br>2 No|
|Perceptions about Corruption|Wp146|Is corruption widespread within<br>government?|1 Yes<br>2 No|
|Perceptions about Corruption|Wp6267|Do you think the level of<br>corruption in this country is lower,<br>about the same or higher than it<br>|1 Same or lower<br>2 Higher|
|||was 5 years ago?||
|Cronyism|Wp128|Can people in this country get<br>ahead by working hard or not?|1 Yes<br>2 No|
|Quality of jobs|Wp133|<br>Are you satisfied or dissatisfied<br>with efforts to increase the<br>number of quality jobs?|1 Yes<br>2 No|
|Quality of jobs|Wp89|<br>Thinking about the job situation in|1 Good time|
|<br>(Alternative specification)||<br>the city or area where you live<br>today, would you say that it is now<br>a good time or a bad time to find a<br>job?|2 Bad time|
|Satisfaction with education|Wp93|<br>In the city or area where you live,<br>are you satisfied or dissatisfied<br>with the education system or the<br>schools?|1 Approve<br>2 Disapprove|

30
|**Category: Other control**<br>**variables**|**Personal**<br>**information**|||
|---|---|---|---|
|Gender|Wp1219||1 Male<br>2 Female|
|Age<br>Marital children = Computed<br>from marital status and number of<br>children|Wp1220<br>Marital_children|Combination to Wp 1223 and Wp<br>1230|Until 99<br>1 Married with<br>children<br>2 Married without<br>children<br>3 Single with children<br>4 Single without<br>children<br>5 S/D/W with<br>children<br>6 S/D/W without<br>children|
|Marital status<br>(Index construction)|Wp1223|What is your current marital<br>status?|<br>1 Single/never been<br>married<br>2 Married<br>|
||||3 Separated/|
||||<br>divorced/ widowed|
|Number of children<br>(Index construction)|Wp1230|How many children under 15<br>years of age are now living in your<br>household?||
|Religion|religion||1 Muslim<br>2 Non-Muslim/other|
|Migration status|Wp4657|Were you born in this country, or<br>not?|religion<br>1 Born in this country<br>2 Born in another<br>country|
|Level of education|wp3117||<br>1 Completed<br>elementary education<br>or less<br>2 Secondary - 3 year<br>tertiary secondary<br>3 Completed four<br>years of education<br>beyond high school<br>and/or received a 4-<br>year college degree|
|Employment status|emp_2010||<br>1 Employed full time<br>for an employer/<br>Employed part time/<br>do not want full time<br>2 Employed full time<br>for self<br>3 Unemployed<br>4 Out of workforce 5<br>Underemployed<br>6 Other|
|Government employee|Wp1227|Are you a government worker or<br>not?|1 Other<br>2 Yes<br>3 Undetermined|
|Household composition Adults|Wp12|Including yourself, how many<br>people who are residents of age 15<br>or over currently live in this<br>household?|<br>1 One<br>2 Two<br>3 More than two|
|Household income (US$,<br>thousands)<br>Month andyear of Interview|inc_001<br>m_year||Expressed in<br>international dollars|

**Appendix B2: Descriptive Statistics**

31
|**Variable**|**Observations**|**Mean**|**SD**|**Min.**|**Max.**|
|---|---|---|---|---|---|
|Life evaluation|25,244|5.09|2.00|0|10|
|Dissatisfied with standard of living:|25,244|0.37|.48|0|1|
|Yes||||||
|People cannot get ahead by working|25,244|0.17|.37|0|1|
|hard: Yes||||||
|Dissatisfied with efforts to increase|25,244|0.66|.47|0|1|
|with high quality jobs: Yes||||||
|Dissatisfied with freedom to choose<br>|25,244|0.38|.48|0|1|
|life: Yes||||||
|Dissatisfied with the educational<br>|25,244|0.37|.48|0|1|
|system or the schools: Yes||||||
|Corruption widespread within|25,244|0.78|.41|0|1|
|government*: Yes||||||
|Self-employed|25,244|0.08|0.27|0|1|
|<br>Unemployed|25,244|0.04|0.20|0|1|
|<br>Out of workforce|25,244|0.31|0.46|0|1|
|Underemployed|<br>25,244|0.03|0.18|0|1|
|Other**|25,244|0.25|0.43|0|1|
|Government worker|<br>25,244|0.09|0.29|0|1|
|Undetermined|<br>25,244|0.28|0.45|0|1|
|Not Muslim|25,244|0.07|0.26|0|1|
|Completed 9-15 years of education|25,244|0.48|0.49|0|1|
|Completed four years of education|25,244|0.11|0.31|0|1|
|beyond high school and/or 4-year<br>college degree||||||
|Migrant|25,244|0.02|0.15|0|1|
|Income (1,000s)|25,244|10.16|12.20|0|229.99|
|<br>Female|25,244|0.48|0.49|0|1|
|Age|25,244|35.23|14.54|15|99|
|Age squared|25,244|1,453.04|1,210.98|15|99|
|Married without children|25,244|0.15|0.35|225|9,801|
|Single with children|25,244|0.20|0.40|0|1|
|Single without children|25,244|0.17|0.37|0|1|
|<br>Separated/divorced/widow with|25,244|0.03|0.17|0|1|
|children||||||
|Separated/divorced/widow without|25,244|0.26|0.16|0|1|
|children||||||
|2 people older than 15 years in<br>household|25,244|0.23|0.42|0|1|
|More than 2 people older than 15|25,244|0.73|0.45|0|1|
|years in household||||||
|<br>**Alternative Measures**||||||
|Index_fs|21,376|0.41|0.67|0|2|
|Bad time to find a job: Yes|23,592|0.71|0.46|0|1|
|<br>Are levels of corruption higher: Yes|10,926|0.55|0.65|0|1|
|<br>Index positive affect|12,582|64.11|29.09|0|100|
|Index negative affect|4,739|33.13|29.96|0|100|
|Dissatisfaction with health: Yes|11,016|0.16|0.36|0|1|

32
# **Appendix B3: Correlation Matrix**

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|(13)|(14)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Life evaluation|1.00||||||||||||||
|Dissatisfaction with standard of living: Yes|-0.36|1.00|||||||||||||
|People cannot get ahead by working hard:<br>Yes|-0.09|0.16|1.00||||||||||||
|Dissatisfied with efforts to increase high<br>quality jobs: Yes|-0.13|0.19|0.14|1.00|||||||||||
|Dissatisfied with freedom to choose life:<br>Yes|-0.10|0.16|0.16|0.33|1.00||||||||||
|Dissatisfied with educational system|-0.13|0.16|0.09|0.17|0.17|1.00|||||||||
|Corruption widespread within government:<br>Yes|-0.07|0.10|0.07|0.19|0.11|0.13|1.00||||||||
|Income (1,000’s)|0.22|-0.16|-0.01|-0.07|-0.08|-0.09|0.00|1.00|||||||
|Self-employed|0.00|0.00|0.00|0.01|-0.02|-0.01|0.02|0.08|1.00||||||
|Unemployed|-0.07|0.09|0.04|0.05|0.04|0.03|0.00|-0.05|-0.06|1.00|||||
|Out of workforce|-0.03|0.01|-0.01|0.03|0.04|-0.02|-0.02|-0.07|-0.20|-0.14|1.00||||
|Underemployed|-0.04|0.07|0.02|0.03|0.02|0.04|0.01|-0.03|-0.06|-0.04|-0.13|1.00|||
|Government employee|0.04|-0.04|-0.03|-0.03|-0.01|0.02|-0.03|0.01|-0.04|-0.07|-0.22|0.04|1.00||
|Undetermined|0.05|-0.02|0.03|-0.04|0.00|-0.01|0.00|-0.04|-0.12|-0.13|-0.42|0.02|-0.20|1.00|

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# **Appendix C1: Robustness Analysis: Omitted Variable Bias**

Our analysis possibly suffers from simultaneity and omitted variable biases. It is well known that in survey research happier respondents, or those who are in a better mood during an interview, have a tendency to report more positively about different aspects of their life. For example, the amount of negative feelings one experiences during the day could possibly predispose people to lower their life satisfaction rating. When evaluating their satisfaction, respondents can reason as follows: “I am generally dissatisfied with my life, so apparently I am dissatisfied with my government” or “I feel sad now, so apparently I am dissatisfied with my government” (see also Diener 1984; Headey, Veerhoven, and Wearing 1991).

We use different strategies to cope with these problems in our baseline OLS analysis in model 7. First, we control for mood during the interview, by including (1) interview date dummies, assuming that turbulent time indicators of satisfaction can be subject to daily developments; (2) affect indices by Gallup related to very recent positive<sup>13</sup> and negative experiences<sup>14</sup> measured on a 0-100 scale; and (3) satisfaction with health measured on a 0-10 scale. This way we are able to capture the daily mood of individuals, which may affect the responses related to satisfaction.

Table C1 shows the results of these additional robustness checks. The effects of dissatisfaction with the standard of living, income, and employment status remain significant and robust to controlling for interview dates, mood, and health satisfaction. Likewise, perceptions of inequality of opportunity, corruption, and crony capitalism remain an important source of dissatisfaction in developing MENA, where the dissatisfaction with not being able to get ahead by working hard and feelings about corruption in government are negative and statistically significant in most specifications.

In general, the inclusion of interview dates (column 1) or satisfaction with health (column 4) does not affect the main conclusions drawn from the results presented in table 2. However, when we add a negative experience index to our baseline regression, the coefficient for unemployed is reduced and becomes statistically insignificant (column 3). To some extent, this also reflects the

> 13 The Gallup positive experience index is based on the following five questions: (1) “Did you feel well-rested yesterday?” (2) “Were you treated with respect all day yesterday?” (3) “Did you smile or laugh a lot yesterday?” (4) “Did you learn or do something interesting yesterday?” and (5) “Did you experience the following feelings during a lot of the day yesterday? How about enjoyment?”

> 14 The Gallup negative experience index is based on the following five feelings, which respondents had to reflect on based on the question: “Did you experience the following feelings during a lot of the day yesterday?: physical pain, worry, sadness, stress, and anger.”

34
fact that when we include the experience index, the sample size is reduced from 25,244 to 6,221 respondents.

# **Table C1: Determinants of Life Satisfaction in Developing MENA in Alternative Models (OLS)**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|VARIABLES|+Interview<br>Dates|+ Positive<br>Experience<br>Index|+ Negative<br>Experience<br>Index|+ Satisfaction<br>with Health|
|Dissatisfied with freedom to choose<br>|-0.039<br>|-0.019<br>|-0.022<br>|-0.046<br>|
|life: Yes|(0.030)|(0.036)|(0.044)|(0.048)|
|Dissatisfaction with standard of living:|-1.242***|-1.103***|-1.124***|-1.055***|
|Yes|(0.030)|(0.037)|(0.044)|(0.046)|
|Income (1,000’s)|0.023***|0.020***|0.022***|0.019***|
||(0.002)|(0.002)|(0.002)|(0.002)|
|Dissatisfied with efforts to increase|-0.155***|-0.101***|-0.089*|-0.108**|
|high quality jobs: Yes|(0.032)|(0.037)|(0.046)|(0.050)|
|Dissatisfied with the educational|-0.169***|-0.115***|-0.099**|-0.142***|
|system or the schools: Yes|(0.029)|(0.035)|(0.043)|(0.045)|
|Corruption widespread within|-0.083**|-0.104**|-0.127**|-0.080|
|government: Yes|(0.035)|(0.042)|(0.050)|(0.056)|
|People cannot get ahead by working|-0.238***|-0.228***|-0.199***|-0.340***|
|hard: Yes|(0.039)|(0.047)|(0.055)|(0.061)|
|Positive experience index||0.007***<br>(0.001)|||
|Negative experience index|||-0.007***<br>(0.001)||
|Dissatisfied with personal health: Yes||||-0.369***<br>(0.060)|
|Self-employed|0.054|0.113|-0.012|0.141*|
||(0.061)|(0.079)|(0.117)|(0.081)|
|Unemployed|-0.352***|-0.234**|-0.112|-0.291***|
||(0.078)|(0.103)|(0.137)|(0.105)|
|Out of workforce|-0.027|-0.005|-0.053|0.017|
||(0.047)|(0.058)|(0.088)|(0.065)|
|Underemployed|-0.138*|-0.087|-0.141|-0.180*|
||(0.080)|(0.097)|(0.166)|(0.101)|
|Individual characteristics|YES|YES|YES|YES|
|Country fixed effects|YES|YES<sup>A</sup>|YES<sup>B</sup>|YES<sup>A</sup>|
|Month and year of interview|NO|YES|YES|YES|
|Constant|5.839***|5.420***|6.221***|6.013***|
||(0.198)|(0.207)|(0.250)|(0.246)|
|Observations|25,244|18,442|12,582|11,016|
|R-squared|0.230|0.201|0.198|0.191|

_Note:_ Robust standard errors are in parentheses. *** p < .01, ** p < .05, * p < .1. A Morocco missing.

B Morocco and Tunisia missing.

35
# **Appendix C2: Robustness Analysis: Heterogeneity within Developing MENA**

The developing MENA region encompasses a wide variety of Arab countries. Hence, the correlates of dissatisfaction with life might differ across countries. In our robustness analysis, we distinguish between (1) North Africa, (2) Middle East, (3) Levant (including and excluding Iraq), and (4) Iraq.

**Table C2: Determinants of Life Satisfaction in Developing MENA by Subregion (OLS)**

|VARIABLES|(1)<br>North<br>Africa<sup>A</sup>|(2)<br>Middle<br>East<sup>B</sup>|(3)<br>Levant Area 1<sup>C</sup>|(4)<br>Levant Area 2<sup>D</sup>|(5)<br>Iraq|
|---|---|---|---|---|---|
|Dissatisfied with freedom to|0.017|-0.077*|-0.115**|-0.078*|-0.052|
|choose life: Yes|(0.041)|(0.043)|(0.055)|(0.044)|(0.079)|
|Dissatisfaction with standard of|-1.211***|-1.246***|-1.295***|-1.204***|-0.657***|
|living: Yes|(0.042)|(0.040)|(0.052)|(0.043)|(0.081)|
|Income (1,000s)|0.023***<br>(0.002)|0.022***<br>(0.003)|0.018***<br>(0.003)|0.021***<br>(0.003)|0.064***<br>(0.015)|
|Dissatisfied with efforts to increase<br>with high quality jobs: Yes|-0.117***<br>(0.039)|-0.192***<br>(0.048)|-0.096<br>(0.061)|-0.190***<br>(0.050)|-0.334***<br>(0.098)|
|<br>Dissatisfied with the educational|<br>-0.218***|<br>-0.144***|<br>-0.148***|<br>-0.181***|<br>-0.285***|
|system or the schools: Yes|(0.039)|(0.041)|(0.054)|(0.043)|(0.080)|
|Corruption widespread within<br>Y|-0.079*|-0.078|0.029|-0.082|-0.472***|
|government: es||||||
||(0.044)|(0.052)|(0.062)|(0.052)|(0.114)|
|People cannot get ahead by<br>ki hd Y|-0.209***|-0.233***|-0.283***|-0.245***|-0.172**|
|worng ar: es||||||
||(0.060)|(0.048)|(0.061)|(0.049)|(0.084)|
|Self-employed|0.380***<br>(0.085)|-0.143*<br>(0.083)|-0.209*<br>(0.107)|-0.115<br>(0.087)|0.105<br>(0.145)|
|Unemployed|-0.168|-0.437***|-0.576***|-0.368***|-0.220|
||(0.106)|(0.111)|(0.156)|(0.114)|(0.184)|
|Out of workforce|-0.011|-0.048|0.017|-0.009|-0.193|
||(0.061)|(0.071)|(0.087)|(0.073)|(0.154)|
|Underemployed|-0.098|-0.167|-0.185|-0.158|-0.148|
||(0.131)|(0.102)|(0.148)|(0.116)|(0.175)|
|Other|0.170***|0.269***|0.226**|0.202**|0.114|
||(0.065)|(0.088)|(0.103)|(0.081)|(0.181)|
|Individual characteristics|YES|YES|YES|YES|YES|
|Country fixed effects|YES|YES|YES|YES|YES|
|Month and year of interview|YES|YES|YES|YES|YES|
|<br>Constant|6.142***|5.956***|6.226***|5.561***|5.291***|
||(0.223)|(0.243)|(0.297)|(0.246)|(0.911)|
|Observations|10,444|14,800|9,184|13,244|2,432|
|R-squared|0.249|0.188|0.206|0.180|0.174|

_Note:_ Robust standard errors are in parentheses. ***p < .01; **p < .05; *p < .10. A North Africa includes Morocco, Algeria, Tunisia, Libya, and Egypt. B Middle East includes Syria, Palestine, Jordan, Lebanon, the Republic of Yemen, and Iraq. C Levant 1 includes Syria, Palestine, Jordan, and Lebanon. D Levant 2 includes Syria, Palestine, Jordan, Lebanon, Egypt, and Iraq.

Table C2 shows the results of the subsample analyses, where three findings stand out. First, the socioeconomic correlates of satisfaction with life are fairly consistent across different groupings of countries in the developing MENA region. Second, satisfaction with freedom to choose life is not 36
equally important for determining life evaluation. In North Africa (column 1) and Iraq (column 5), the effect of freedom has no significant value, while the most significant effect of satisfaction with freedom can be found in the Levant area (column 3). Third, the association between widespread corruption and life satisfaction is very sensitive to the selection of countries. The effect of widespread corruption is only negative and statistically significant for North Africa and Iraq.

# **Appendix C3: Robustness Analysis: Alternative Variable Specifications**

In addition, we performed several robustness controls to verify the significance of our findings. Table C3 shows five alternative specifications. In specification 1, satisfaction with the standard of living is measured by the Gallup Food and Shelter Index, which is based on the question whether individuals experienced a shortage of money to provide food and shelter for their family. In specification 2, dissatisfaction with efforts to increase the number of high quality jobs is replaced by job expectations measured based on answers to the question: “ _Thinking about the job situation in the city or area where you live today, would you say that it is now a good time or a bad time to find a job?_ ” In specification 3, autocracy and lack of democracy are captured by a variable related to freedom and integrity of the media based on the question: “ _Do you have confidence in the quality and integrity of the media?”_ Corruption was alternatively measured in specification 4 by perceptions about changes in the levels of corruption over the past years (“ _Do you think the level of corruption in this country is lower, about the same or higher than it was 5 years ago?”_ ).

Table C3 shows the results for the regressions using the alternative variable definitions. The results are not directly comparable with the results in table 2, since the alternative variables are not available for some countries and/or waves. Still, the results in table C3 show that our conclusions regarding dissatisfaction with the standard of living and job opportunities as important drivers of life dissatisfaction in developing MENA generally hold, while freedom is again found not to be important for explaining life dissatisfaction in developing MENA. Although perceptions of increased corruption seem to be associated with life satisfaction in developing MENA, its effect is smaller compared with the rest of the alternative measures reported in table C3. The effect of feelings of not being able to get ahead by working hard and dissatisfaction with the education system remains statistically significant across all specifications.

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# **Table C3: Determinants of Life Satisfaction in developing MENA: Alternative Variable Specifications (OLS)**

|VARIABLES|(1)<br>Alternative<br>standards of<br>living|(2)<br>Alternative<br>job<br>opportunities|(3)<br>Alternative<br>civil freedom|(4)<br>Alternative<br>widespread<br>corruption|
|---|---|---|---|---|
|Food and Shelter Index|-0.976***<br>(0.059)||||
|Would you say that it is now a good<br>time or a bad time to find a job: Bad<br>time||-0.141***<br>(0.033)|||
|Do you have confidence in each of the|||-0.029||
|following? How about the quality and<br>integrity of the media: No|||(0.042)||
|Level of corruption is higher||||-0.081***|
|People cannot get ahead by working<br>hard: Yes|-0.305***<br>(0.042)|-0.195***<br>(0.040)|-0.225***<br>(0.057)|-0.200***<br>(0.039)|
|Dissatisfied with the educational<br>system or the schools: Yes|-0.252***<br>(0.034)|-0.150***<br>(0.031)|-0.166***<br>(0.043)|-0.169***<br>(0.030)|
|Individual characteristics|YES|YES|YES|YES|
|Country fixed effects|YES<sup>A</sup>|YES<sup>B</sup>|YES|YES|
|Month and year of interview|YES|YES|YES|YES|
|Constant|6.470***|5.865***|5.902***|5.676***|
||(0.200)|(0.180)|(0.267)|(0.177)|
|**Observations**|21,376|23,592|10,926|24,012|
|R-squared|0.162|0.207|0.220|0.210|

_Note:_ Robust standard errors are in parentheses. ***p < .01; **p < .05; *p < .10.

A Morocco and Syria are missing.

B Morocco is missing.

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# **Appendix D1: Changes in Averages and Decomposition of Effects, Lewbel Estimator**

||Change in<br>the obtained<br>coefficient<br>(2009-10)<br>DEV MENA|Change in<br>the obtained<br>coefficient<br>(2009-10)<br>ArabSpring|Change in<br>the averages<br>(2009-10)<br>DEV MENA|Change in<br>the averages<br>(2009-10)<br>ArabSpring|Developing<br>MENA<br>first-order<br>effect|Developing<br>MENA<br>second-order<br>effect|Arab Spring<br>countries<br>first-order<br>effect|Arab Spring<br>counties<br>second -order<br>effect|
|---|---|---|---|---|---|---|---|---|
|Dissatisfaction with|0.101|0.015|0.028|0.091|-0.031|0.037|-0.084|0.005|
|Standards of living|||||||||
|People cannot get ahead by<br>working hard (Yes)|0.213|0.120|-0.012|0.004|0.005|0.038|-0.001|0.012|
|Dissatisfaction with efforts<br>of the government to|0.033|-0.098|0.033|0.070|-0.012|0.021|-0.030|-0.060|
|increase high quality jobs|||||||||
|Dissatisfaction with|-0.199|-0.058|0.038|0.052|-0.014|-0.074|-0.015|-0.018|
|freedom to choose life|||||||||
|Dissatisfaction with<br>educational system/schools|1.000|0.910|-0.015|0.076|-0.007|0.382|0.029|0.331|
|Corruption widespread<br>within government/|-0.113|-0.387|0.016|0.111|-0.008|-0.088|-0.040|-0.262|
|business (Yes)<br>Unemployed|0.393|0.179|0.001|0.030|0.000|0.025|-0.012|0.004|
|Working for the|0.339|0.481|0.038|0.034|0.013|0.022|0.020|0.043|
|government|||||||||
|Income (1,000’s)|0.001|-0.009|-0.600|-1.306|-0.015|0.010|-0.025|-0.077|

39
# **Appendix D2: Changes in Averages and Decomposition of Effects, OLS**

||Change in<br>the obtained<br>coefficient<br>(2009-10)<br>DEVMENA|Change in<br>the obtained<br>coefficient<br>(2009-10)<br>Arab Spring|Change in<br>the averages<br>(2009-10)<br>DEV<br>MENA|Change in<br>the averages<br>(2009-10)<br>Arab Spring|Developing<br>MENAA<br>first-order<br>effect|Developing<br>MENA<br>second-order<br>effect|Arab Spring<br>countries<br>first-order<br>effect|Arab Spring<br>counties (4)<br>second -order<br>effect|
|---|---|---|---|---|---|---|---|---|
|Dissatisfaction with|0,064|0,072|0,028|0,091|-0,033|0,024|-0,106|0,023|
|Standards of living|||||||||
|People cannot get ahead by<br>working hard (Yes)|-0,033|-0,027|-0,012|0,004|0,003|-0,006|-0,001|-0,003|
|Dissatisfaction with efforts<br>of the government to<br>increase high quality jobs|-0,010|-0,024|0,033|0,070|-0,005|-0,007|-0,011|-0,015|
|Dissatisfaction with freedom|0,050|0,265|0,038|0,052|-0,001|0,019|0,006|0,083|
|to choose life|||||||||
|Dissatisfaction with|-0,006|0,014|-0,015|0,076|0,002|-0,002|-0,012|0,005|
|Educational system/schools|||||||||
|Corruption widespread<br>within government/business|0,043|-0,317|0,016|0,111|-0,001|0,033|-0,027|-0,215|
|(Yes)<br>Unemployed|0,258|0,339|0,001|0,030|0,000|0,017|-0,009|0,008|
|Working for the government|0,298|0,542|0,038|0,034|0,013|0,019|0,020|0,049|
|Income (1,000’s)|0,001|-0,011|-0,600|-1,306|-0,014|0,010|-0,025|-0,094|

40