Measuring the Spatial Correlation of Unemployment in Iraq-2007
Faisal G. Khamis
AL-Zaytoonah University of Jordan, Faculty of Economics and Administrative Sciences
PO box 130, Amman 11733, Jordan
Tel: 962-7-9594-7494 E-mail: faisal_alshamari@yahoo.com
Received: August 19, 2011 Accepted: October 12, 2011 Published: January 1, 2012
doi:10.5539/mas.v6n1p17 URL: http://dx.doi.org/10.5539/mas.v6n1p17
Modern Applied Science Vol. 6, No. 1; January 2012
Abstract
Although many studies examined the existence of spatial pattern of unemployment in some developing and many developed countries in improving the prosperity or social status and reducing the inequalities in unemployment between areas of such country, there is still much work to be done. Some of these studies were found spatial pattern for unemployment using different statistical techniques and geographical mapping. Question is raised whether the spatial pattern of unemployment is existed in Iraq? The objective is to investigate the spatial structure of unemployment rate (UR) across different governorates to provide implications for policy makers, investigating the hot spots of UR, and showing visual picture for UR. The study utilized a cross-sectional census data for 18 governorates collected in 2007. Mapping was used as a first step to conduct visual inspection for UR using quartiles. Two statistics of spatial autocorrelation, based on sharing boundary neighbours, known as global and local Moran's I, were carried out for examining the global clustering and local clusters respectively. Based on visual inspection of mapping, the global clustering was found in UR and it was confirmed by the significant statistic found by global Moran’s I. Out of 18, seven governorates: 3, 4, 5, 12, 15, 16, and 17 were found as local clusters in UR based on local Moran's Ii. In conclusion, the UR was found to vary across different governorates with black spots in northern and southern parts of the country.
Keywords: Spatial autocorrelation, Unemployment, Mapping, Moran statistic, Iraqgovernorates, Neighbours
1. Introduction
Unemployment is one of the main socioeconomic issues, which negatively affects both economic activity and social life. In recent years, there has been a growing interest in examining the existence of spatial autocorrelation of UR and its spatial relationship to many indicators such as poverty, education, etc. High unemployment, poverty, and weak social protection systems dominate public concerns and threaten fragile democracy (Poortman, et al., 2006).
It is well known in the literature that UR tends to vary systematically between regions. Partridge and Rickman (1997) found significant levels of dispersion in U.S. state UR in 1970s and 1990s. Evans and McCormick (1994) studied changes in the regional pattern of unemployment in UK since the 1970s. Utilizing results from OECD studies, they begin their analysis with the observation that regional unemployment differentials have been strikingly persistent for a very long period, both in UK and in other OECD countries. Evidence provided by Eichengreen (1993) indicated that the responsiveness of unemployment differentials was much greater in US than in Europe. Bertola (1999), as well as Balu and Kahn (1999), analyzed the impact of different institutions and regulations on labour market outcomes. According to their results, wage adjustment and labour mobility were affected by minimum-wage provisions unemployment benefits and welfare payments. However, the results of Layard (1997) implied that strict labour market regulations, employment protection and minimum wages not be the main target areas of policies aiming at a significant decline of unemployment. Instead they advised reform of social security systems combined with active labour market policies. In US, URs remain near a 25-year high and global unemployment is rising (Roelfs, et al., 2011). Unemployment can affect both psychological (Ezzy, 1993) and physiological (Arnetz, et al., 1991) risk factors for ill health. These effects may be mediated by various factors, such as changes in social support (Kong, Perrucci, & Perrucci, 1993) and altered alcohol and tobacco consumption (Janlert, 1997). Downward social class mobility and financial hardship may also affect health negatively and partly explain some of the increased mortality among individuals who are not employed (Whelan, 1992). Unemployment may interfere with one’s social relationships, and increase the risk of divorce (Lester, 1996) which may in turn influence the risk of mortality (Lester, 2001). Elhorst (2003) provided a review of the unemployment disparities literature. Blanchard and Katz (1992) discussed mechanisms which can operate to close such disparities. The three primary mechanisms were wage adjustments, outmigration of unemployed workers, and the movement of firms into low-wage/ high-unemployment areas.
In Iraq unemployment remains at very high levels, where themost population groups affected by unemployment were women and youth (Agency for technical cooperation and development, 2010). Epilepsy is a chronic illness that affects all ages in Iraq, specifically in Salahuddin governorate, which has long-term complications such as impairment of employability as stated by AL-Saad, et al. (2001). Unemployment in this governorate was found 33% and this rate was significantly greater among those stricken by epilepsy especially the young. Youth unemployment was high and increasing: 57% of those aged between 15 and 29 are unemployed and 450000 new young men are entering the labour market each year (UNIAU Iraq labour force analysis 2003-2008). About one in every ten Iraqis was living in absolute poverty according to best available estimates and another one in every seven or eight is at risk of falling into absolute poverty. Those most vulnerable include the unemployed, who make up about 30% of the laboure force and more than 50% of urban youths, and others (legions of demobilized soldiers and ex-militia, war victims, the refugees, displaced persons and returnees). The labor force participation rate among Iraqi youth was estimated at less than 30%, while for the economy as a whole it is over 40% (Ministry of Planning and Development Cooperation/UNDP, 2005). Unemployment early in working life has been shown to increase the probability of future joblessness and lower future wages and can lead to alienation and social unrest (ILO, 1998–99). While reconstruction and associated public-sector jobs are important in the initial phase of Iraq’s recovery, they will not create a sufficient number of jobs to meet the population’s needs in the long term, even if recovery is on a massive scale (World Bank, 2006). Employed young men are less likely to participate in political violence, implying a positive correlation between unemployment and violence in locations with active insurgencies (Eli, et al., 2011). Eli et al. tested that prediction in Afghanistan, Iraq, and Philippines, where they didn’t find significant relationship between unemployment and the rate of insurgent attacks that kill civilians.
A common feature of most of the above mentioned studies is that they investigated the functioning of labour market adjustments and the effects of labour market regulations without considering the spatial dimension of area labour market disparities. Most of these studies have shown that unemployed persons have an increased risk of death. Some studies investigated the wage curve taking spatial effects into account. Manning (1994) and Buettner (1999) analyzed the relationship between earnings and unemployment for British countries and German regions respectively. An analysis by Molho (1995) confirmed that there is significant spatial interaction among regional labour markets in UK. Overman and Puga (2002) analyzed unemployment clusters across European regions. The results of their nonparametric approach indicted that URs were much more homogeneous across neighbouring areas than across regions in the same EU country. The results found by Filiztekin (2007) indicated that the provincial URs were quite persistent and the gap across different regions widens further with spatial clusters emerging across Turkey. Lopez-Bazo, Barrio, and Artis (2001) discussed the role of neighbouring effects in explaining the spatial distribution of unemployment, where their results pointed to the emergence of at least two clusters in the regional distribution of UR in Spain. Massimo and Fabio (2011) examined and measured the efficiency of Italian policies for labour market carried out in the last 10 years, in terms of reduction in the regional disparities in comparison with the whole European distribution of unemployment. Massimo and Fabio showed that Italy has still a prominent role in the geographical disparities among regions and that its contribution to the geographical concentration of unemployment is still high.
To understand the linkages between socioeconomic variables, investigation should focus on features of the areas rather than on the compositional characteristics of residents of the area, which cannot fully describe the social environment in which people live (Macintyre, Maciver, & Sooman, 1993). So, spatial autocorrelation and geographical pattern of URs were studied by the author. Spatial autocorrelation is the term used for the interdependence of the values of a variable over space. However, it was argued that lattice data are spatially correlated, where exploratory spatial data analysis (ESDA) was used using lattice data. The ESDA quantifies the spatial pattern in order to increase the analyst's knowledge of the spatial system. As well as mapping plays an important role in the monitoring of unemployed people. Maps can reveal spatial patterns not previously recognized or suspected from the examination of a table of statistics and reveal high risk communities or problem areas (Lawson & Williams, 2001). The purpose of spatial analysis is to identify pattern in geographic data and attempt to explain this pattern. Findings are expected to enhance unemployment monitoring and policing interventions across governorates in Iraq
Low wage flexibility and limited labour mobility involve persistent unemployment differentials across governorates in Iraq. The present paper focuses on the spatial structure of unemployment disparities across governorates. Governorates are tightly linked by migration, commuting, and inter-governorate trade. These types of spatial interaction are exposed to the frictional effects of distance, possibly causing the spatial dependence of governorate labour market conditions. Governorates marked by high or low unemployment tend to cluster in space.
Reducing unemployment inequalities was not primary objective but emergent prosperity. The importance of the goal or the purpose of the present paper was followed from such argument stated that unemployment is a standard indicator for poverty status of the population. Cattaneo (2006) stated that a strong link existed between poverty and unemployment, being the lack of employment one of the main determinants of poverty. According to the study in Jordan by Amerah (1993), health was affected negatively by unemployment, where Amerah stated that since the mid-1980s unemployment had become a serious problem in Jordan, manifesting a widening gap between the demand for and supply of labour. Elhorst (2003) proposed several reasons that make studying the spatially uneven distribution of unemployment worthwhile. One of these reasons is the wide unemployment differentials imply inefficiency in the economy as a whole and reduces growth. Yip and Caine (2011) examined the complex relationships between suicide rates and regional unemployment rates during 2000-6 in Hong Kong, where they found strong correlation (0.86). Furthermore, to author's knowledge no studies used the spatial analysis techniques and geographical mapping in studying the inequalities in unemployment gradient in Iraq. Furthermore, the studies that used other advanced statistical techniques, such as structural equations modeling, in examining the inequalities of unemployment were very limited in Iraq.
The importance of mapping was stated by Koch (2005): Why make the map if detailed statistical tables carry the same results? Perhaps the most important reason for studying spatial statistics is not only interested in answering the "how much" question, but the "how much is where" question (Schabenberger&Gotway, 2005). In light of these: (1) the existence of spatial global clustering, (2) spatial local clusters of governorates with respect to UR were investigated, and (3) mapping was applied for transformed UR and for its local Moran’s i I values. This study contributes to the literature by examining the geographical distribution of UR, spatial global clustering and local clusters of unemployment. The study design was a cross-section analysis in a census survey conducted in Iraq in 2007.In conclusion, no spatial global clustering in UR was found, but local clusters were found. The major contribution was the demonstration that spatial locations have statistically significant effects on the likelihood and disparity of UR.
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