Corresponding author: Goran Miladinov ( miladinovg@aol.com ) © 2021 Goran Miladinov.
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Citation:
Miladinov G (2021) Impact of unemployment by sex and marriage rate on fertility decline: Estimates for Turkey and Greece using CCR model. Population and Economics 5(3): 76-89. https://doi.org/10.3897/popecon.5.e69189
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The article analyses the effect of unemployment by sex and marriage rate on fertility changes in Greece and Turkey. The empirical part of the study is based on annual time series data retrieved from the World Bank and National Statistical Offices of Turkey and Greece for 1991–2019. Canonical Cointegrating Regression model is applied for the two countries separately, allowing to quantify the effects of the determinants (crude marriage rate and unemployment rate by sex) on the variation of fertility rate. CCR models show these determinants to be the most significant factors of fertility dynamics in both countries. The results from Engle-Granger and the Phillips-Ouliaris tau (t-statistics) tests confirm the cointegration, i.e., long-term relationship between the variables only for Turkey’s CCR model. However, it was found that in Greece, female unemployment impacts fertility rate negatively and male unemployment has a positive effect on fertility rate; for Turkey modelling shows the opposite relationship. The results of the study suggest that economic uncertainties might be one of the factors contributing to fertility decline in these countries, long-term or in the coming years.
TFR, CMR, unemployment rate by sex, Canonical Cointegrating Regression, Turkey, Greece
The political and socioeconomic environment in a country is shaped by important national and international forces, such as the development of market economy or globalization, which have different effects in different ways across countries and societies (
The aim of this study is to carry out an independent country analysis for two Mediterranean countries (Turkey and Greece) in terms of fertility changes and unemployment and marriage context within the last three decades. These two countries represent different fertility transition patterns. Turkey and Greece differ in more than one respect: the beginning of fertility transition in these countries started at different times, it followed different ways and paces, and at this very moment these countries display different rates of fertility decline. Turkey experienced the earliest drop in fertility in the 1950s, and by the end of the twentieth century the fertility was already approaching the replacement level (
To be precise, the goal of this article is to study whether the decline in fertility observed in Turkey and Greece (the countries are considered separately, without comparison) could be related to the interplay between the labour market uncertainty and fertility dynamics. Implications of this study might gain more importance after the institution of marriage transforms along with the global structural development process in the economic and demographic domains (for instance, urbanization, industrialization, and modernization in a wider perspective). This analysis covers several key research questions about the fertility, economic uncertainties, and labour market, namely: Have economic uncertainties been a less important fertility factor decades ago than they are now? Have gender inequalities on a labour market lessened? Is marriage status still important factor of fertility?
The article is organized as follows: section 2 contains the theoretical background of the research; section 3 presents data and methodology of the study; section 4 reviews the empirical results of the study; section 5 provides discussion and summarizes the key concluding remarks of the research.
Most of the demographic theories appear to be explaining fertility processes, such as the questions why fertility declines over time, what leads women to give birth, and why there is a negative relationship between fertility and family income (
Citing the Giddens’ theory of structuration, from 2013,
The empirical part of this study bases on annual time series data retrieved from World Bank indicators database (World Bank 2020) for the period 1991–2019. Additionally, the data for Turkish and Greek TFR for 2019 and data for the Turkish marriage rate for the whole period of study were obtained from National Statistical offices of the countries, Turkish Statistical Institute (2020, 2014) and Hellenic Statistical Authority (2020), respectively — due to the lack of these data within UN and World Bank databases. In order to have methodologically standardized data for both countries, the estimations of the World Bank about Total Fertility Rate (TFR) for these countries have been used as well. These estimations of the World Bank are based mainly on the following sources: United Nations database; census reports and other statistical publications from national statistical offices; Eurostat database and international database of the U.S. Census Bureau.
We should make some remarks on the methodological comparability of the data covering the two countries under review. Thus, the TFR series for Turkey is the average of expert estimates and simulations based on a variety of approaches, i.e., estimates based on indirect methods. The TFR series for Greece is a direct calculation based on official birth registration statistics and annual estimates of the number of women by one-year age group. Hence, in spite of the fact that the data are taken from the same database (the World Bank), this does not ensure their methodological comparability. For this reason, the country analysis in this study is carried out independently, the author avoids comparing countries.
The variable of interest is total fertility rate, measured as the number of live births per woman.
One of the independent variables is crude marriage rate (CMR), which is measured as a number of marriages per 1,000 persons. In the family demography, analysis of marriages, i.e. measure of the trend of marriage rate is simply used as an indicator of family formation and/or behavior. Marital status is an important source of information on the family (Bartolini, Bilancini and Pugno 2013) and marriage is considered an important institution (
Another independent variable is unemployment rate by sex. The perception of financial security is seen as a significant prerequisite for having children (
In order to understand the impact of the economic and demographic indicators on the total fertility rate and to explain the variation of the fertility rate in Turkey and Greece, the author applies cointegrating regression. Figures
Regarding the cointegrating relationships, Engle and Granger have noted that a linear combination of two or more I(1) series can be stationary, or I(0), in which case it could be said that the series are cointegrated (IHS 2017). This kind of a linear combination defines a cointegrating equation with cointegrating vectors of weights indicating the long-run relationship between the variables. This study applies a Canonical Cointegrating Regression (CCR), which represents the same cointegrating relationships as the original models. Anyhow, CCR models are constructed in such a way that the regular least squares procedure generates asymptotically efficient estimators and chi-square tests (
If one of our explanatory variables is correlated with the error term, then the assumption of E = (εixi) = 0 is not valid (
Following IHS guidelines (2017: 276), first thing to do when using the CCR model is to get the estimations of the innovations uˆt = (uˆ1t, uˆ´2t)´ and appropriate constant estimations of the long-run covariance matrices Ωˆand Λˆ Differently from FMOLS, CCR needs additionally a consistent estimator of the contemporaneous covariance matrix Σˆ. The columns of Λˆ that are consistent with the one-sided long-run covariance matrix of uˆt and (the levels and lags of) uˆ2t are removed.
The transformation of (y1t, Xt´) have been performed by using the formulas as in (2) and (3), respectively:
where the βˆ are estimates of the cointegrating equation coefficients, thus, these are usually the standard OLS estimates employed to get the residuals uˆ1t (IHS 2017). Therefore, CCR estimators could be defined as ordinary least squares applied on the transformed data.
where Z*t = (Zt*´, D1t*´)´
When estimating the specification by CCR for Turkey, a prewhitened Quadratic-spectral kernel estimators of the long-run covariance matrices was applied. Thus, the calculation method was changed and a (fixed lag) VAR(1) was specified for the prewhitening method, so the kernel shape was changed to quadratic spectral. The first thing that was noted was that the VAR prewhitening within Turkish CCR model had a stronger effect on the kernel part of the calculation of the long-run covariances. Furthermore, as a result of prewhitening, the estimate of the conditional long-run variance has changed quite a bit. Differences aside, this contributed to smaller standard errors of the estimated coefficients for CCR. All of this was not possible to do when estimating the specification by CCR for Greece. Instead, for the Greek CCR model the Bartlett kernel estimator of the long-run covariance matrices was used and a lag was not specified within the calculation method. The estimates of the regressors equations are in differenced form.
Total fertility rate, Greece and Turkey, 1991–2019. Source: Author’s estimates based on various sources
Crude marriage rate per 1,000, Greece and Turkey, 1991–2019. Source: Author’s esctimates based on various sources
A Canonical Cointegrating Regression (CCR) model was estimated that includes additional deterministics in the cointegrating regression equations, i.e. intercept and @TREND. Our empirical results are acquired by using aggregate annual data for total fertility rate (TFR) and crude marriage rate (CMR), as well as female unemployment rate and male unemployment rate as percentage of the female and male labour force, respectively, for Greece and Turkey from 1991 to 2019. The estimated coefficients, the standard errors, t-statistic, and p-value for the estimated coefficients, the constant and trend values as well as summary statistics are presented in Tables
Crude marriage rate has no significant effect on total fertility rate for Greek CCR model, but other variables do have a significant effect on fertility rate at 5% and 1% level of significance. For Greece, the female unemployment rate has the most significant (negative) impact on fertility rate. The impact of male unemployment is also significant but with positive signs. All included variables in the CCR model for Turkey are significant at 5% and 1%. The most significant (positive) effect on fertility rate is the female unemployment rate. In the Turkish CCR model, both male unemployment rate and the crude marriage rate have a statistically significant (negative) effect on fertility rate.
Consequently, our test of the null hypothesis of no cointegration against the alternative of cointegration is consistent with a unit root test of the null of non stationarity against the alternative of stationarity. Resuming with our CCR model of TFR and CMR as well as unemployment by sex, Engle-Granger and Phillips-Ouliaris tests were constructed from an estimated equation where the deterministic regressors include a constant and linear trend. It is confirmed that Engle-Granger and Phillips-Ouliaris tests are computed using C and @TREND as deterministic regressors, and it is also noted that the option to include a lagged difference in the ADF regression was determined using automatic lag selection with a Schwarz criterion (IHS 2017). For that reason, the asymptotic distributions of the Engle-Granger and Phillips-Ouliaris τ and z statistics are non-standard and depend on the deterministic regressors specification, thus the critical values for the statistics are obtained from simulation results. These two tests contradict the method of interpreting for serial correlation in the residual series. Therefore, the Engle-Granger test uses a parametric, augmented Dickey-Fuller (ADF) approach, while the Phillips-Ouliaris test uses the non-parametric Phillips-Perron (PP) method. Our test results showed that the Engle-Granger tau-statistic (t-statistic) did reject the null hypothesis of no cointegration (unit root in the residuals) at the 5% level only for Turkey. Accordingly, the tau-statistic did not reject the null hypothesis of no cointegration for Greece. The normalized autocorrelation coefficient (which is termed the z-statistic) did not reject the null hypothesis of no cointegration (unit root in the residuals) at the 5% level for any of the countries. Hence, the evidence from these tests clearly suggests that TFR and CMR as well as unemployment rate by sex are cointegrated for Turkey, but not for Greece (Tables
Variable | Coefficient | Std. Error | t-Statistics | Prob. |
Crude marriage rate | -0.0090 | 0.0390 | -0.2301 | 0.8201 |
Female unemployment rate | -0.0560 | 0.0080 | -6.9909 | 0.0000 |
Male unemployment rate | 0.0468 | 0.0079 | 5.9335 | 0.0000 |
C | 1.8544 | 0.2534 | 7.3165 | 0.0000 |
@TREND | 0.0053 | 0.0018 | 2.9493 | 0.0072 |
Summary statistics | ||||
R-squared | 0.7739 | |||
Adjusted R-squared | 0.7346 | |||
S.E. of Regression | 0.0386 | |||
Long-run variance | 0.0014 | |||
Mean dependent var | 1.3332 | |||
S.D. dependent var | 0.0748 | |||
Sum squared resid | 0.0342 | |||
Cointegration Tests | ||||
Engle-Granger tau statistics Value | -3.5130 | |||
Prob. | 0.4091 | |||
Engle-Granger z-statistics Value | -17.8216 | |||
Prob. | 0.3801 | |||
Philips-Ouliaris tau statistics Value | -3.4653 | |||
Prob. | 0.4298 | |||
Philips-Ouliaris z-statistics Value | 15.7760 | |||
Prob. | 0.5166 |
Variable | Coefficient | Std. Error | t-Statistics | Prob. |
Crude marriage rate | -0.0580 | 0.0100 | -5.7918 | 0.0000 |
Female unemployment rate | 0.0637 | 0.0080 | 8.0077 | 0.0000 |
Male unemployment rate | -0.0469 | 0.0080 | -5.8920 | 0.0000 |
C | 3.2741 | 0.0738 | 44.377 | 0.0000 |
@TREND | -0.0464 | 0.0016 | -28.378 | 0.0000 |
Summary statistics | ||||
R-squared | 0.9837 | |||
Adjusted R-squared | 0.9808 | |||
S.E. of Regression | 0.0384 | |||
Long-run variance | 0.0008 | |||
Mean dependent var | 2.3593 | |||
S.D. dependent var | 0.2772 | |||
Sum squared resid | 0.0339 | |||
Cointegration Tests | ||||
Engle-Granger tau statistics Value | -5.2844 | |||
Prob. | 0.0286 | |||
Engle-Granger z-statistics Value | -20.2056 | |||
Prob. | 0.2447 | |||
Philips-Ouliaris tau statistics Value | -5.3259 | |||
Prob. | 0.0265 | |||
Philips-Ouliaris z-statistics Value | -20.7365 | |||
Prob. | 0.2191 |
This paper highlights the great importance of fertility decline analysis in relation with unemployment rate by sex and marriage rate. The distinctions are noticed separately for two countries, Turkey and Greece, suggesting in general that the economic surroundings and inequalities play a significant role in the process of fertility decline.
In our case, Engle-Granger tau-statistic (t-statistic) for Turkey has shown that the null hypothesis of cointegration is rejected. For Greece, none of the performed tests rejected the null hypothesis. These results indicate that there is no cointegration relationship between model variables for Greece. Therefore, the hypothesis of the study is partially accepted, i.e., the long-term cointegration between model variables was found only for Turkey, but not for Greece.
The results obtained for Turkish case imply that there is some kind of mutual mechanism between these series in the long-run, since the process of convergence is perceived. This provided a determination of the long-term coefficient between the variables by the CCR method as a tool to examine the importance of the cointegration relationship between these time series. In other words, marriage status and the consequences of unemployment by sex and in consequence of TFR are captured by our cointegration model (CCR) which determines feasible interactions between each variable used by this model. Taken separately, these findings confirm suggestions that the CCR model is a powerful estimator of examining the fertility decline for Turkey.
Table
The results of the study have a few implications in economic and socio-demographic sense for Turkey. Firstly, the female unemployed status on the labour market in Turkey has exceptionally strong impact on the decision to have a child. In addition, the fact that Turkey is a very heterogeneous society may be one of the key challenges for policymakers to embrace a different strategy to improve the quality of life of the people. At the same time, it is important to mitigate the risk of labour market uncertainties for the long run since it is necessary for higher employment rates and in consequence it may induce the increase of TFR. In a society where there are contrasts between conventional and alternative behaviors, as was stated by
A CCR model estimated for Greece has not shown any cointegrating relationship between the variables (Table
Our results for Greece however still reveal a relationship that we cannot neglect, even though the different effect of the unemployment by sex on fertility requires more operative and systematic methodologies that should be justified within future research. Maybe an announcement for more substantial and deeper reforms of public policies for structural economic investments and social protection are the endogenous factors that may explain these conflicting results for Greece.
To define further, our results point to the well-known difficulties of balancing between reproduction career and socioeconomic context in modern societies (
The author is very grateful to the anonymous reviewers for their valuable comments on this paper.
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Goran Miladinov, PhD in Demography from Faculty of Economics, Ss. Cyril and Methodius university. E-mail: miladinovg@aol.com