The role of macroeconomic factors in shaping employment trends in Somalia

Mohamed, Abdikadir Ahmed; Abdulle, Abdikani Yusuf; Omar, Mahdi Mohamed Article The role of macroeconomic factors in shaping employment trends in Somalia Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Mohamed, Abdikadir Ahmed; Abdulle, Abdikani Yusuf; Omar, Mahdi Mohamed (2024) : The role of macroeconomic factors in shaping employment trends in Somalia, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 12, Iss. 1, pp. 1-16, https://doi.org/10.1080/23322039.2024.2416989 This Version is available at: https://hdl.handle.net/10419/321633 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Economics & Finance ISSN: 2332-2039 (Online) Journal homepage: www.tandfonline.com/journals/oaef20 The role of macroeconomic factors in shaping employment trends in Somalia Abdikadir Ahmed Mohamed, Abdikani Yusuf Abdulle & Mahdi Mohamed Omar To cite this article: Abdikadir Ahmed Mohamed, Abdikani Yusuf Abdulle & Mahdi Mohamed Omar (2024) The role of macroeconomic factors in shaping employment trends in Somalia, Cogent Economics & Finance, 12:1, 2416989, DOI: 10.1080/23322039.2024.2416989 To link to this article: https://doi.org/10.1080/23322039.2024.2416989 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 20 Oct 2024. Submit your article to this journal Article views: 1623 View related articles View Crossmark data Citing articles: 1 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE The role of macroeconomic factors in shaping employment trends in Somalia Abdikadir Ahmed Mohamed , Abdikani Yusuf Abdulle and Mahdi Mohamed Omar Faculty of Economics and Management, Jamhuriya University of Science and Technology, Mogadishu, Somalia ABSTRACT Somalia has one of the most severe unemployment rates globally, due to its economic instability. Our study focuses on the macroeconomic effects on employment using an ARDL model. The key macroeconomic variables examined are GDP, inflation, FDI, foreign aid, and population growth, with data sourced from the World Bank spanning 32years, from 1991 to 2022. The study found that GDP positively affects employment in both the short and long run. Inflation shows a positive correlation with employment in the short run but a negative effect but insignificant in the long run. FDI has a positive effect in the long run and a negative, insignificant effect in the short run. Foreign aid positively impacts employment in both the short and long run, though the effect is not significant in the latter. the study recommends policies to sustain economic growth, manage population growth, stabilize prices, and improve aid management to enhance employment opportunities in Somalia. IMPACT STATEMENT This research examines the macroeconomic determinants of employment in Somalia, focusing on the effects of economic growth, inflation, foreign direct investment (FDI), foreign aid, and population growth from 1991 to 2022. Using an ARDL model, the study provides both short-term and long-term insights into how these factors influence employment trends. The findings underscore the positive role of GDP growth and foreign aid in promoting employment, while highlighting the negative impact of rapid population growth on job creation. This work is significant as it offers targeted policy recommendations to address Somalia’s unemployment challenges, emphasizing the need for sectoral diversification, improved governance of foreign aid, and strategies to stabilize FDI flows. The study provides a vital contribution to the limited literature on Somalia’s employment dynamics and serves as a guide for policymakers working to foster sustainable economic growth and job creation. ARTICLE HISTORY Received 25 July 2024 Revised 18 September 2024 Accepted 10 October 2024 KEYWORDS Employment; economic growth; inflation; FDI; population growth; macroeconomic; ARDL; Somalia SUBJECTS Macroeconomics; Economics; Economic Forecasting Introduction Employment is a key indicator of economic health, defined by the World Bank as the fraction of the population aged 15 and older that is employed (World Bank, 2024). However, global employment trends remain challenging, with the International Labour Organization (ILO) projecting a modest rise in unemployment for 2024, particularly in low-income countries where poverty and unemployment rates are persistently high (ILO, 2024). Africa’s employment landscape has been shaped by uneven economic growth, driven by factors such as natural resource endowments, political stability, and infrastructure development (Adekunle et al., 2023). While Foreign Direct Investment (FDI) in Africa has increased, particularly in natural resources and telecommunications, its overall share of global FDI remains small due to challenges like political instability and regulatory uncertainties (Asiedu, 2002). Similarly, foreign aid plays a crucial role in funding development projects, but its impact on economic growth and employment is often mixed due to governance and corruption issues (Moyo, 2009). Inflation, which varies CONTACT Abdikadir Ahmed Mohamed [email protected] Faculty of Economics and Management, Jamhuriya University of Science and Technology, Mogadishu, Somalia. ß2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. COGENT ECONOMICS & FINANCE 2024, VOL. 12, NO. 1, 2416989 https://doi.org/10.1080/23322039.2024.2416989 widely across African countries, is driven by factors like currency fluctuations and fiscal policies, often posing a challenge to economic stability in countries with weaker institutions (Fedelino & Ter-Minassian, 2009). Stylized facts on employment and macroeconomic variables Somalia, in particular, has faced significant economic challenges due to decades of political instability, conflict, and a lack of central governance following the collapse of the government in 1991 (Menkhaus, 2007,2014). This instability has led to the disintegration of formal economic institutions, severely disrupting economic activities and employment opportunities. As of 2023, Somalia’s unemployment rate stands at 19.19%, one of the highest globally, with the country struggling to create sufficient job opportunities, especially for its large youth population (UNDP, 2024; World Bank, 2023). Somalia’s economy is heavily reliant on agriculture, particularly livestock production, which makes up a significant portion of GDP. However, this sector is highly vulnerable to climate variability, including frequent droughts and erratic rainfall patterns that threaten food security and disrupt rural employment opportunities (Warsame et al., 2022). Despite these challenges, Somalia has seen modest economic growth in recent years, with GDP growth rates improving from 2.4% in 2022 to 3.7% in 2023, and further growth anticipated in 2024 with the completion of the debt relief process (African Development Bank Group, 2024). Foreign direct investment (FDI) has also played a crucial role in Somalia’s economic recovery. In 2022, Somalia attracted USD 4.9 billion in FDI, primarily in sectors such as agriculture, livestock, fishing, and hydrocarbons (Lloyds Bank, 2024). However, FDI remains volatile due to political instability and weak regulatory frameworks, making the business environment unpredictable. Additionally, Somalia ranks among the top recipients of foreign aid globally, with foreign aid financing two-thirds of the national budget (BTI, 2024). While foreign aid is essential for supporting key sectors like healthcare, education, and infrastructure, its impact on sustainable job creation has been limited, often undermined by governance challenges and inefficiencies (Moyo, 2009). Inflation has been another persistent challenge for Somalia, fluctuating due to weak fiscal management and currency instability. Although inflation rates are projected to decline to 5.21% in 2024, previous high inflation has eroded purchasing power and complicated efforts to reduce unemployment (African Development Bank Group, 2024). Meanwhile, Somalia’s population growth rate, estimated at 3.2% in 2024, adds further pressure on the economy (World Population Review, 2024). With 70% of the population under the age of 30, the labor market faces significant challenges in absorbing this rapidly expanding young workforce, contributing to widespread youth unemployment. Macroeconomic stability, economic growth, and low inflation are key drivers of employment creation (International Monetary Fund, & World Bank, 2024). Factors such as FDI (Tanveer et al., 2019), foreign aid, and controlled population growth also play an essential role in fostering an environment conducive to employment generation (Forte & Abreu, 2023). Countries that enjoy such favorable macroeconomic conditions often experience sustained economic development, lower unemployment, and improved social well-being (Pieloch-Babiarz et al., 2021). However, in Somalia, employment conditions remain challenging, with the country continuing to rank among those with the highest unemployment rates in the world (Maow, 2021). While there has been substantial research on how individual macroeconomic factors such as economic growth, inflation, and FDI affect employment in various contexts (Meyer & Sanusi, 2019; Nguyen, 2024; Nguyen et al., 2024), limited research has focused on the combined effects of these factors on employment in Somalia. This gap in the literature is critical, as understanding the interaction of multiple macroeconomic variables is essential for developing targeted policies that can address Somalia’s unique employment challenges. This study seeks to fill this gap by utilizing an Autoregressive Distributed Lag (ARDL) model to analyze the relationships between economic growth, inflation, FDI, foreign aid, and population growth on employment in Somalia. By employing time series data from the World Bank, the study will provide insights that can help policymakers design effective strategies to increase employment opportunities and promote sustainable economic growth in Somalia. 2 A. A. MOHAMED ET AL. Literature review The relationship between macroeconomic factors and employment trends has been widely studied in both developed and developing countries. However, research integrating multiple macroeconomic variables to assess their collective impact on employment, particularly in Somalia, remains limited. This literature review explores how economic growth, inflation, foreign direct investment (FDI), foreign aid, and population growth affect employment, forming the basis for this study. Theoretical framework Economic theories provide diverse predictions regarding the impact of macroeconomic factors on employment. According to Keynesian economics, economic growth drives employment by stimulating demand for goods and services. Keynes argued that during economic expansions, increased consumer demand leads to higher production, which in turn creates more jobs (Auerbach & Gorodnichenko, 2017). Conversely, the Phillips Curve posits a short-term tradeoff between inflation and unemployment, where higher inflation results in lower unemployment in the short run (Phillips, 1958). However, this relationship disappears in the long run, according to some empirical findings. Foreign Direct Investment (FDI) is another critical macroeconomic variable influencing employment. Dunning’s Eclectic Paradigm (OLI Model) suggests that FDI boosts employment through the inflow of capital, advanced technology, and managerial expertise (Dunning, 2015). However, the extent to which FDI positively affects employment depends on how well the domestic economy can absorb these benefits. Similarly, Aid Effectiveness Theory (Burnside & Dollar, 2000) argues that foreign aid can promote employment by funding infrastructure, education, and health projects. However, the effectiveness of foreign aid depends on proper management, with corruption or inefficiencies often reducing its impact. Finally, Demographic Transition Theory explains how population growth affects employment across different stages of development. Rapid population growth may lead to a surplus labor force, which, if not absorbed by the economy, can result in high unemployment (Galor, 2012). Empirical evidence Several studies highlight the relationship between economic growth and employment, though the strength of this relationship varies across contexts. (Mushtaq et al., 2022) employed panel data analysis to assess the impact of economic growth on employment across Asian countries show and found that economic growth significantly boosts employment in Asian countries. However, the panel data approach may obscure country-specific factors, which are critical in fragile economies like Somalia. (Haider et al., 2023) used a structural vector autoregression (SVAR) model to show that in developing countries, GDP growth does not always lead to proportional employment gains, a phenomenon known as ‘jobless growth’. However, the SVAR model assumes shocks are exogenous, which may not apply to Somalia, where political instability is likely an internal factor affecting both growth and employment. (Meyer & Sanusi, 2019) applied a causality test to identify a bi-directional relationship between growth and employment in South Africa, but this method does not account for long-term structural challenges like the informal economy, which is highly relevant to Somalia’s employment landscape. (Bluedorn, 2013) discuss the volatility of capital flows and how this impacts employment, a pertinent issue in Somalia given its political instability and reliance on foreign investment. Somalia’s economy, like many other fragile economies, faces challenges in maintaining stable capital flows, which undermines sustainable job creation. These studies collectively highlight that while economic growth can drive employment, the unique context of Somalia, characterized by instability, may require a more tailored approach that addresses structural deficiencies beyond growth. The Phillips Curve suggests a tradeoff between inflation and unemployment, but its validity has been questioned, particularly in developing economies. (Camara et al., 2023) employed an econometric model analyzing inflation rates and employment across Sub-Saharan Africa, showing that inflation above 14% has a significantly negative impact on employment. Their study uses a fixed threshold for inflation, but COGENT ECONOMICS & FINANCE 3 this may not account for country-specific nuances in inflation dynamics. Somalia, with its history of currency volatility, may experience inflation differently, meaning a dynamic model would be more appropriate. (Angelov, 2023) explored the non-linear effects of inflation on employment using a generalized additive model (GAM), which offers flexibility in modeling relationships. This method is more suitable for Somalia’s volatile inflation environment, as it does not assume a linear relationship. The variation in methodological approaches highlights the complexity of applying generalized inflation models to fragile economies like Somalia, where inflationary pressures are more volatile. Foreign Direct Investment (FDI) is widely recognized as a catalyst for employment, but the long-term stability of its impact in fragile economies remains contested. (Nguyen et al., 2024) employed a panel data analysis, showing that FDI positively impacts both highand low-skilled employment by introducing advanced technologies and managerial expertise. However, their reliance on panel data averages out country-specific variations, which might downplay the role of volatility in fragile economies like Somalia. (Rong et al., 2020) used a sectoral analysis approach, showing that FDI supports job creation in labor-intensive industries. This method, though useful, does not consider the instability of capital flows in fragile contexts like Somalia, (Afolabi & Raifu, 2024) used a sectoral analysis approach to show that FDI promotes employment in labor-intensive sectors, particularly in developing economies. This finding is highly relevant for Somalia, where FDI flows into agriculture, livestock, and hydrocarbons—sectors that are labor-intensive and vital for employment. However, despite this positive impact, (Bluedorn, 2013) and (Chletsos & Sintos, 2021) caution that in fragile economies like Somalia, capital flows and financial fragility can limit the long-term benefits of FDI on employment. (Chletsos & Sintos, 2021) specifically examine the role of financial fragility in economically vulnerable countries and its direct effects on employment. Their findings suggest that without addressing underlying financial instability, the employment benefits of FDI in fragile states can be short-lived or unstable. This insight is crucial for Somalia, where political and financial instability may undermine the potential gains from FDI. Foreign aid plays a crucial role in employment creation by financing infrastructure and development projects. (Tanveer et al., 2019) used a cross-country panel regression to examine the effects of aid on employment. While their findings are generally positive, cross-country regressions can suffer from omitted variable bias, particularly when governance quality and corruption major issues in Somalia are not fully accounted for. (Mart ınez-Zarzoso et al., 2016) found that foreign aid can positively impact development outcomes when country-specific factors are considered. However, their fixed-effects model may not fully account for governance challenges, such as corruption, which are particularly relevant to Somalia and can distort aid effectiveness. (Gnangnon, 2020) applied a time-series analysis to study how ‘Aid for Trade’programs can promote employment diversification in fragile economies. This method is more context-specific and thus better suited to Somalia, where sectoral diversification is crucial for stability. However, the challenges of governance and corruption, as noted by Chletsos and Sintos (2023), in their analysis of IMF programs, remain a key limitation in ensuring the effectiveness of aid in Somalia. These studies suggest that while aid can promote employment, its impact is contingent on governance quality, which remains a persistent challenge in Somalia. Somalia’s rapid population growth poses both opportunities and challenges for employment creation. (Adeosun & Popogbe, 2021) used a linear regression model to show that rapid population growth exacerbates unemployment when job creation does not keep pace. While linear models provide a clear picture, they may oversimplify the relationship between population growth and employment by not accounting for complex dynamics like labor market saturation or migration. (Mushtaq et al., 2022) confirm these findings but use panel data, which, as mentioned earlier, can obscure specific national contexts. (Ngai & Petrongolo, 2017) used a sectoral model to explore the rise of the service economy and its implications for gendered employment patterns. This approach is more relevant for Somalia as the country seeks to diversify away from agriculture. However, the application of their findings to Somalia requires careful consideration, as the country’s economic infrastructure may not yet support the scale of service-sector growth seen in more stable economies. (Kluve et al., 2019), provide a meta-analysis on youth employment programs, using a wide range of methodological approaches. Their meta-analysis is particularly relevant for Somalia, given the country’s high youth unemployment rate, but the generalizability of their findings to fragile states like Somalia may be limited due to governance and institutional 4 A. A. MOHAMED ET AL. differences. These studies suggest that population growth poses a critical challenge for employment creation, and targeted policies, particularly youth employment programs, are essential. The review of the literature highlights the complex relationship between macroeconomic factors such as GDP growth, inflation, FDI, foreign aid, population growth, and employment. While existing research offers valuable insights into how these factors influence employment, limited research has focused on Somalia, a country with unique political and economic challenges. This study aims to fill this gap by using an Autoregressive Distributed Lag (ARDL) model to analyze the short-term and long-term effects of these macroeconomic factors on employment trends in Somalia. Methodology This study utilizes time series data from the World Bank, covering the period from 1991 to 2022. This period captures the critical phases of political instability, economic recovery, and international interventions, allowing for an analysis of macroeconomic factors and their impact on employment. The period was chosen because data for several key variables are unavailable before 1991 and after 2022. This timeframe provides the most reliable and complete dataset for accurate analysis of macroeconomic factors and employment trends in Somalia. It examines the relationship between variables such as economic growth (GDP), inflation (INF), foreign direct investment (FDI), foreign aid (FAID), and population growth (PG) with employment in Somalia. Table 1 provides a summary of the key variables used in the analysis, including their measurements and sources. Autoregressive Distributed Lag (ARDL) model selected to analyze both the short-term and long-term relationships between the variables. This approach allows us to examine how selected macroeconomic variables impact employment over different time periods. The ARDL model was chosen for this study due to its ability to handle both short-term and long-term relationships between variables, which is essential for analyzing Somalia’s macroeconomic data. Unlike Johansen’s cointegration method, which requires all variables to be integrated at the same level, ARDL accommodates variables that are a mix of I(0) and I(1). It also performs well with small sample sizes, making it suitable for this study’s 32-year dataset. Additionally, ARDL allows for flexible lag selection, enabling more accurate insights into how variables like FDI, inflation, and aid affect employment over time. The model’s use of the Bounds Testing approach for cointegration further enhances its suitability, allowing for the detection of long-term relationships in mixed-order datasets. Overall, ARDL offers the flexibility and robustness needed to analyze the complex dynamics of macroeconomic factors and employment in Somalia. The mathematical formulation of the ARDL model is as follows: EMP ¼GDPt,þINFt,þFDIt,þFAIDt,þPGt(1) Based on the empirical work of Sarkodie and Adams (2018), the ARDL co-integration equation can be formulated as follows: EMPt¼a0þb1GDPt−1þb2INFt−1þb3FDIt−1þb4FAIDt−1þþb5PGt−1þXq i¼0Da1GDPt−k þXp i¼0Da2INFt−kþXp i¼0Da3FDIt−kþXq i¼0Da4FAIDt−kþXq i¼0Da5PGt−kþet Where a0represents the constant term, a1,a2,a3,a4,a5are the coefficient of the short-run variables, b1,b2b3,b4and b5represent the elasticities of the long-run parameters, the symbol q denotes the Table 1. Source and measurement. Variables Measurements Sources Employment (EMP) Employment-to-population ratio (% of population ages 15þ) World Bank Economic Growth GDP growth (annual %) World Bank Inflation (INF) Inflation, GDP deflator (annual %) World Bank Foreign direct investment (FDI) Foreign direct investment, net inflows (BoP, current US$) World Bank Foreign Aid (FAID) Net official development assistance received (current US$) World Bank Population Growth (PG) Annual population growth (%) World Bank Note. Data compiled by the authors from the World Bank. COGENT ECONOMICS & FINANCE 5 optimal lags of the dependent variable, while p indicates the optimal lags of the independent variables, Dsignifies the first difference, representing the short-run variables, and et is the error term. Our analysis starts with a unit root test. Then, we will perform the ARDL model to test the long-term and short-term relationships between the variables. Finally, we will conduct diagnostic and stability tests, specifically focusing on serial correlation, heteroskedasticity, and normality tests. The macro economic factors, inclouding GDP, inflation, FDI, foreign aid, and population growth are expected to have significant impacts on employment. Economic growth is typically associated with positive employment effects (Mushtaq et al., 2022), while inflation’s impact can be mixed, influencing purchasing power and cost of living (Angelov, 2023). FDI is expected to boost job creation (Rong et al., 2020), foreign aid can support employment through infrastructure and development projects (Tanveer et al., 2019), and population growth affects labor supply and demand dynamics (Adeosun & Popogbe, 2021). Data limitations While this study relies on macroeconomic data from the World Bank (1991–2022), several limitations must be acknowledged, especially considering Somalia’s political and economic instability. Somalia’s volatile political environment and weak institutions may lead to gaps and inaccuracies in the data, particularly due to difficulties in capturing the informal economy, which forms a large part of the country’s economic activities. The employment data, based on the employment-to-population ratio, may not fully capture informal employment. Additionally, much of the data for Somalia is modeled, leading to potential inaccuracies in reflecting the actual employment situation. Periods of political instability, such as during the civil war, may have resulted in incomplete or estimated data, particularly in earlier years. Missing values or unreliable estimations from these periods may affect the precision of the study’s analysis. FDI and foreign aid data may not always capture smaller investments or account for aid disbursements tied to political objectives, which may not directly contribute to employment growth. Given the potential data gaps, assumptions were made in the analysis, especially regarding data stationarity and the non-causal relationship between variables like FDI and employment. This limits the precision of the study’s findings. Results Table 2 provides a summary of the descriptive statistics for the key variables in this study, including employment (EMP), economic growth (GDP), inflation (INF), foreign direct investment (FDI), foreign aid (FAID), and population growth (PG). Employment (EMP) shows a mean of 5.85, with low variability (standard deviation of 0.42), and a slight negative skewness, indicating a left-skewed distribution. Economic growth (GDP) reveals significant variability (standard deviation of 5.58) and a pronounced left skew (−2.47), reflecting periods of negative growth common in volatile economies. Inflation (INF) presents a mean of 13.17% with high variability, indicating periods of extreme inflation, while FDI Table 2. Descriptive statistics (Compiled by the authors by using EViews 12). EMP GDP INF FDI FAID PG Mean 5.852967 4.330558 13.170520 1.54E þ08 8.03E þ08 2.881176 Median 6.030650 6.694352 7.309868 91500000. 5.94E þ08 3.431286 Maximum 6.276559 9.946800 55.814750 6.36E þ08 3.04E þ09 4.994928 Minimum 5.049702 −17.846990 −15.346900 −479000.0 81180000 −4.629117 Std. Dev. 0.418555 5.575870 16.390170 1.98E þ08 7.54E þ08 2.132495 Skewness −0.625337 −2.465537 1.004091 1.119993 1.188856 −3.004375 Kurtosis 1.874380 9.527304 3.692919 28.73513 27.84964 11.401080 Jarque-Bera 3.774943 89.228260 6.017246 6.690078 8.631796 142.244300 Probability 0.151454 0.000000 0.049360 0.035259 0.013355 0.000000 Sum 187.294900 138.577900 421.456800 4.92E þ09 2.57E þ10 92.197650 Sum Sq. Dev. 5.430844 963.800000 8327.772000 1.21E þ18 1.76E þ19 122.039500 Observations 32 32 32 32 32 32 6 A. A. MOHAMED ET AL. displays substantial variability (standard deviation of $198 million), suggesting large fluctuations in net inflows. Similarly, foreign aid (FAID) has a right-skewed distribution, with an average of $803 million in annual aid, marked by significant variability (standard deviation of $754 million). Population growth (PG) shows a left-skewed distribution with a mean of 2.88% and significant variability. The Jarque-Bera test results indicate that several variables deviate from normality, especially GDP, FDI, and FAID, which exhibit leptokurtic distributions, signaling extreme values and distributional outliers. These results underscore the need for caution when applying methods that assume normal distributions, particularly given the volatility of macroeconomic variables in Somalia. The unit root tests using the Augmented Dickey-Fuller (ADF) tes in Table 3 determine the stationarity of each variable at both the level and first difference. The null hypothesis (H0) for these tests is that the series has a unit root (i.e. the series is non-stationary), while the alternative hypothesis (H1) is that the series does not have a unit root (i.e. the series is stationary). The results indicate that economic growth (GDP) and population growth (PG) are stationary at the level for both intercept and trend & intercept, signifying they are integrated of order I(0) and rejecting the null hypothesis at the level. Conversely, inflation (INF), foreign direct investment (FDI), and foreign aid (FAID) are not stationary at the level but become stationary at the first difference, indicating they are integrated of order I(1) and rejecting the null hypothesis at the first difference. Employment (EMP), however, is not stationary at both the level and first difference. These mixed integration orders for the variables justify the use of the ARDL model to explore both short-term and long-term relationships among the variables. Further analysis will involve the ARDL bounds test to check for cointegration and subsequently estimating the ARDL model to derive significant insights into the dynamics affecting employment in Somalia. The Spearman correlation in Table 4 results reveal that EMP has a strong positive correlation with FDI, indicating that higher levels of foreign direct investment are associated with increased employment. Conversely, there is a strong negative correlation between EMP and INF, suggesting that higher inflation tends to decrease employment levels. GDP shows a moderate positive correlation with EMP, implying that economic growth supports employment. These findings provide a foundational understanding of how these macroeconomic factors impact employment in Somalia. The next step is to estimate the ARDL model to quantify the short-term and long-term effects of these independent variables on employment, given the established cointegration. Contigration test The ARDL bounds test is used to determine whether a long-term relationship (cointegration) exists between the variables in the model. The test compares the calculated F-statistic to the lower and upper critical values at various significance levels (1%, 5%, 10%). If the F-statistic exceeds the upper bound at Table 3. Unit root test (Compiled by the authors by using EViews 12). Variables Level First difference Intercept Trend & intercept Intercept Trend & intercept EMP −2.963972 −3.562882 −2.963972 −3.568379 GDP −2.960411 −3.562882 −2.963972 −3.568379 INF −2.960411 −3.562882 −2.963972 −3.568379 FDI −2.967767 −3.574244 −2.963972 −3.568379 FAID −2.967767 −3.562882 −2.971853 −3.574244 PG −2.960411 −3.562882 −2.963972 −3.568379 Note.  and  symbolize significance at 5% and 1%, respectively. Table 4. Spearman correlation tests (Computed by the authors using EViews 12). EMP GDP INF FDI FAID PG EMP 1.00000000 0.36272980 −0.78666760 0.65936500 0.58467854 0.32607234 GDP 0.36272980 1.00000000 −0.55221360 −0.03652330 −0.16589150 0.22210272 INF −0.7866676 −0.55221360 1.00000000 −0.37090650 −0.28191300 −0.10358480 FDI 0.65936500 −0.03652330 −0.37090650 1.00000000 0.92061756 0.16352740 FAID 0.58467854 −0.16589150 −0.28191300 0.92061756 1.00000000 0.06604884 PG 0.32607234 0.22210272 −0.10358480 0.16352740 0.06604884 1.00000000 COGENT ECONOMICS & FINANCE 7 significantly between Somalia’s agriculture, services, and manufacturing sectors. Conducting sector-specific analyses would allow policymakers to design more targeted interventions aimed at boosting employment in the most vulnerable or promising areas of the economy. Lastly, given the impact of external shocks such as global economic crises, climate change, and international aid fluctuations, future research should also examine how these shocks influence employment dynamics in fragile economies. By incorporating external factors and testing for their impact through vector autoregression (VAR) models or dynamic stochastic general equilibrium (DSGE) models, future studies can provide a more comprehensive picture of how Somalia’s labor market responds to both internal and external pressures. Author contributions Abdikadir Ahmed Mohamed: Conceptualization, Methodology, Data Analysis, Writing - Original Draft Abdikani Yusuf Abdulle: Literature Review, Data Collection, Writing - Review & Editing Mahdi Mohamed Omar: Data Analysis, Writing - Review & Editing All authors have read and approved the final version of the manuscript. Disclosure statement No potential conflict of interest was reported by the author(s). Funding This study received financial support from Jamhuriya University of Science and Technology. About the authors Abdikadir Ahmed Mohamed holds a Bachelor’s degree in Economics from Mogadishu University and a Master of Business Administration from Jamhuriya University of Science and Technology. He is currently affiliated with Jamhuriya University of Science and Technology, where he teaches and conducts research. His research interests encompass foreign aid, environmental studies, migration, and economics. Abdikadir has contributed to various academic papers and projects focused on the economic and environmental challenges facing Somalia, including foreign direct investment, migration dynamics, and sustainable development. Abdikani Yusuf Abdulle holds a Master’s degree in Economics Management from Universiti Sains Malaysia and works at Jamhuriya University of Science and Technology. His research interest include macroeconomics, public economics, and resources and agricultural economics, with a particular focus on the economic development challenges of Somalia. Abdikani’s work explores policy implications for sustainable resource use, agricultural productivity, and fiscal reforms to stimulate long-term economic growth. Mahdi Mohamed Omar is the Dean of the Faculty of Economics and Management at Jamhuriya University. His research interests include climate change, economic growth, sustainable development, and governance. With over 8 years of experience in Somali social, economic, and political affairs, he has contributed to various academic and policy papers in these areas. ORCID Abdikadir Ahmed Mohamed http://orcid.org/0009-0004-7589-8502 Abdikani Yusuf Abdulle http://orcid.org/0000-0002-7739-439X Mahdi Mohamed Omar http://orcid.org/0009-0001-1791-4680 Data availability statement The data and materials used and/or analyzed during the current study are available from the corresponding author upon reasonable request. 14 A. A. MOHAMED ET AL. References Adekunle, I. A., Maku, O., Williams, T., Gbagidi, J., & Ajike, E. O. (2023). 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