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Public Choice
Erschienen in: Public Choice 1-2/2018

26.02.2018

Youth bulges, insurrections and labor-market restrictions

verfasst von: Thomas Apolte, Lena Gerling

Erschienen in: Public Choice | Ausgabe 1-2/2018

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Abstract

This paper analyzes the link between large youth cohorts and violent conflicts when labor-market restrictions are present. Such restrictions are expected to limit the youth cohort’s access to income opportunities in the formal economy, and thus lower the youth-specific opportunity cost of insurrection activities. We develop a theoretical model of insurrection markets and integrate the youth cohort’s relative size. In equilibrium, a binding labor-market constraint interacts with the youth bulge in determining the level of insurrection activities within the society. We test the implications of our model on a sample of 135 non-OECD countries in the post-Cold War period and find the effect of the youth cohort’s relative size on conflict onsets to be moderated by changes in the labor-market conditions as measured by unemployment rates. Generally, the results provide evidence that the underlying institutional setting shapes the conflict potential inherent in a given demographic structure.
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Fußnoten
1
These effects already have been mentioned by Goldstone (1991, p. 139): “If real wages are above average, then ...a youthful population can be stabilizing. However, if there is a precipitous drop in real wages, then ...the youthfulness of the population can increase the mobilization potential of the population”.
 
2
There is by now a vast amount of literature following Acemoglu and Robinson (2000, 2001, 2006) that is based on the notion of collectively sustained revolution constraints (see, e.g., Dorsch and Maarek 2015; Cervellati et al. 2014). However, this literature suffers from a number of drawbacks. In general, the literature on revolutions suppresses the micro-structure of collective action, so that it provides an ex-post rationalization rather than a causal explanation of insurrection activities (Apolte 2012).
 
3
Acemoglu (2006) and Dorsch and Maarek (2015) consider the scope of tax instruments and deadweight-losses from such intervention into the economy. Since they are not critical for the point raised in this paper, we abstract from these losses.
 
4
A detailed formal analysis of the following is provided in the “Appendix”.
 
5
See the “Appendix” for the formal details.
 
6
We rule out possible situations with no labor-market restriction and, at the same time, utility from insurrection activities is less than the net effective wage rate even with full employment, so that insurrection activities are never worthwhile.
 
7
See the “Appendix” for the formal details.
 
8
In the following, we use the terms “insurrection” and “conflict” interchangeably as our (empirical) conflict measure closely resembles what we modeled as “insurrections” in the theoretical section.
 
9
We refrain from relating the youth cohort size to the total population as such a measure might seriously underestimate the extent of a youth bulge in the presence of continued high fertility rates (Urdal 2004, 2006).
 
10
Technically, we use the size of the cohort of the 0-to-9-year-old males at time t-15 [which becomes the youth cohort (aged 15–24) in t]. In the denominator, we include the size of the population aged zero to 54 in t-15 [which becomes the total working population (aged 15–69) in t].
 
11
Similar approaches are applied in studies of the relationship between youth cohorts and labor-market outcomes (Korenman and Neumark 1997) and in the literature on demography and economic growth (see, for example, Bloom and Williamson 1998).
 
12
See Angrist and Krueger (1999) for a technical discussion of this condition.
 
13
We provide an online appendix that contains additional information on the definitions and sources of all variables included in our analysis.
 
14
One concern with the included controls is that they might be endogenous to insurrections and tend to be correlated with each other (Burke et al. 2014). Therefore, we treat these controls with caution and also present results without them. Nevertheless, our results do not depend on the chosen number and definition of the control variables. Additional regression results are available from the authors.
 
15
For a country with RYCS (at birth) at the sample mean (= 0.149), the standardized value of this variable is zero. Thus, the overall effect of a one-unit increase in UE (= unemployment changes) at RYCS (at birth) = 0.149 is simply \(\hat{\gamma _2}\). For a country with RYCS (at birth) = 0.177, the standardized value is 0.848. The overall effect of a one-unit increase in UE at RYCS (at birth) = 0.177 is therefore \(\hat{\gamma _2} + \hat{\gamma _3}*0.848\). The differential effect of a one-unit increase in UE is the difference in both effects, or \(\hat{\gamma _3}*0.848 = 0.00727*0.848 = 0.00616\) (i.e., 0.616 percentage points).
 
16
One could question the extent to which the absence of regulatory constraints actually reflects functioning labor markets. While this might be true for many (though not all) developed countries, in less developed countries the absence of labor regulations could simply reflect the failure of the state to establish a regulatory framework needed for functioning markets in the first place. That is one more reason why we refrain from using these indices as our main labor-market indicators.
 
17
Since the indicator variable does not vary over time and the relative youth cohort size exhibits only little within-country variation, we refrain from including country fixed effects in our model, but instead enter regional and region-year fixed effects.
 
18
In models (3)–(6) of Table 3, we separately include dummy variables for the political system, levels of education and resource rents. For ease of exposition, we summarize the coefficients on the main effects of these variables in one line, and we do the same for the interaction with RYCS (at birth) and the three-way interaction effect, using as a placeholder the term “indicator variable”.
 
19
The results are qualitatively similar if we use the PolityIV definition and define as democratic all country-years with a Polity2 score of more than five.
 
20
The partial effects of an increase in RYCS for a given value of UE in autocracies versus democracies are computed as follows. In autocracies (i.e., when democracy = 0), the effect of RYCS is given by \(0.0647 + 0.0224\times \overline{UE}\). When democracy = 1, the effect of RYCS is \(0.0647 - 0.0660 + (0.0224 - 0.0213)\times \overline{UE} = -\,0.0013 + 0.0011\times \overline{UE}\), which clearly is smaller than the effect in autocracies for any \(\overline{UE}>0\).
 
21
The construction of the binary variables is similar to the institutional indicators in column (1) and (2) of Table 3. The only difference is that we do not construct time-invariant country averages, but use the annual observations to capture expansions in education over time. We use total years of schooling as well as years of tertiary schooling from the dataset of Barro and Lee (2013). To control for endogeneity concerns and since the data are available only for 5-year periods, we lag the variable by 5 years following Campante and Chor (2012).
 
22
Excluding all observations of ongoing conflicts produces a somewhat artificial correlation between current and lagged values of the dependent variable. Therefore, in the dynamic specifications, the dependent variable is coded one for all conflict onsets, while country-years of ongoing conflicts are coded zero, following the coding procedure of Fearon and Laitin (2003). We call this variable “any conflict onset”. In the online appendix, we provide a list of included cases for all conflict definitions.
 
23
We employ the first-difference GMM estimator instead of the system GMM estimator because it involves fewer internal instruments. As instruments, we use lagged levels of the dependent variable, unemployment (changes) and their interaction with the youth bulge, assuming exogeneity for RYCS (at birth). The results do not change when entering internal instruments for this variable as well.
 
24
In the online appendix we provide additional robustness tests to our baseline model. In particular, we show that our results are robust to alternative definitions of the dependent variable and the youth cohort, as well as to different time structures and to the inclusion of additional demographic controls.
 
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Metadaten
Titel
Youth bulges, insurrections and labor-market restrictions
verfasst von
Thomas Apolte
Lena Gerling
Publikationsdatum
26.02.2018
Verlag
Springer US
Erschienen in
Public Choice / Ausgabe 1-2/2018
Print ISSN: 0048-5829
Elektronische ISSN: 1573-7101
DOI
https://doi.org/10.1007/s11127-018-0514-8

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