The role of labour productivity within Algeria's sustainable economic development: Findings from agricultural sector

Zemri, Bouazza Elamine; Khetib, Sidi Mohamed Boumediene Article The role of labour productivity within Algeria's sustainable economic development: Findings from agricultural sector Croatian Review of Economic, Business and Social Statistics (CREBSS) Provided in Cooperation with: Croatian Statistical Association (CSA), Zagreb Suggested Citation: Zemri, Bouazza Elamine; Khetib, Sidi Mohamed Boumediene (2023) : The role of labour productivity within Algeria's sustainable economic development: Findings from agricultural sector, Croatian Review of Economic, Business and Social Statistics (CREBSS), ISSN 2459-5616, Croatian Statistical Association (CSA), Zagreb, Vol. 9, Iss. 2, pp. 93-108, https://doi.org/10.62366/crebss.2023.2.002 This Version is available at: https://hdl.handle.net/10419/323428 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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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-nc-nd/4.0/ Croatian Review of Economic, Business and Social Statistics 93 CREBSS 9(2):93–108 The role of labour productivity within Algeria’s sustainable economic development: Findings from agricultural sector Bouazza Elamine Zemri 1,*and Sidi Mohamed Boumediene Khetib 1 1University of Tlemcen, Department of Economics, POLDEVA Laboratory, Algeria Q ARTICLE TYPE Preliminary communication ARTICLE INFO Received: July 16, 2023 Accepted: December 3, 2023 DOI: 10.62366/crebss.2023.2.002 JEL: C32, J24, O44, Q11 SUMMARY Despite Algeria’s abundant natural resources, achieving sustainable growth and prosperity remains challenging. Amid this, labour productivity within the agricultural sector stands as a silent warrior, holding within its grasp the secrets to propel the Algerian economy forward. Therefore, this study tries to uncover the pivotal role of labour productivity in Algeria’s agricultural sector as a beacon for sustainable economic development. Using an autoregressive distributed lag (ARDL) model from 1990–2021, the results reveal that agricultural gross production value, inflation, and population growth are significant determinants of GDP per capita in the short–run, while agricultural value added per worker also emerges as an essential long–run driver. However, agricultural employment is shown to have an insignificant impact, indicating declines in the sector’s workforce and neglect in recent years. Overall, the analysis confirms the hypotheses of either short–term or long–term connections between labour productivity and sustainable economic development within Algeria’s agricultural sector. These findings illuminate a pathway that suggests revitalising the labour productivity within Algeria’s agricultural sector could be a key lever in transforming Algeria’s economic landscape towards a more prosperous and sustainable future. KEYWORDS agricultural sector, Algeria, ARDL model, labour productivity, sustainable economic development 1. Introduction "Productivity isn’t everything, but in the long run it is almost everything. A country’s ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker" (Batóg and Batóg,2007). Labour productivity has always been a significant aspect of countries’ development strategies. However, in the last decade, the emphasis on this factor has grown exponentially due to its crucial role in stimulating economic growth and optimizing resource utilization. This shift aligns with The United Nations Sustainable ∗Corresponding author ©2023 Copyright of this article is retained by the author(s) This is an open access article under the CC BY–NC–ND 4.0 license 94 Zemri & Khetib Development Goals (SDGs). Today, enhancing labour productivity has become a primary objective for any economy, especially in the agricultural sector. The fundamental presumption is that efficient use of production factors is not only a means of assessing workforce efficiency, but also an indicator of economic progress and welfare (Velasco–Muñoz et al.,2021). Conversely, low agricultural productivity can hinder the path to sustainable economic development by limiting the export potential of agricultural products, and increasing poverty in rural areas (Awokuse and Xie,2015). Several studies, including those by Goła´s (2019), documented thta agriculture can contribute to economic development in a variety of ways, including as a source of income, a driver of economic activity, job creation, and a provider of environmental services. Gollin (2010) and Urgessa (2015) suggests that the rise of labour productivity is especially relevant in the spheres of material production, such agriculture, and it is the foundation of sustained economic growth. Moreover, studies like Hossain (2008); Riley and Bondibene (2016); M´baye (2022); Gusev and Koshkina (2022) demonstrated that improving labour productivity is the key for production growth and development, not just in the agricultural sector but also in the overall development of countries. Nevertheless, in a country that is keen on achieving efficiency in resource allocation, swinging towards an agriculture export–oriented industry and creating opportunities for economic growth and development, in an era where labour productivity is widely recognized as a crucial element in the journey towards achieving sustainable economic development, one cannot fail to notice that the promotion of labour productivity in Algeria’s agricultural sector has been comparatively neglected. Currently, the agricultural sector in Algeria is facing, challenging conditions characterized by a decline in the number of workers and decreased efficiency. Additionally, factors such as the utilization of outdated technology and the impact of climate change have contributed to a reduction in the sector’s added value. Consequently, prioritizing the improvement of labour productivity in the agricultural sector has become crucial, as it can significantly contribute to Algeria’s sustainable economic development. While existing research provides valuable insights into the relationship between labour productivity and sustainable economic development, a significant gap remains regarding the specific case of Algeria’s agricultural sector. This gap is particularly evident in the lack of studies utilizing GDP per capita to measure sustainable economic development, providing a more nuanced understanding of the relationship with labour productivity. This study addresses this research gap by employing econometric models to analyze the long–run and short–run relationship between labour productivity and GDP per capita in Algeria’s agricultural sector. Consequently, this study focuses on the central question: will unlocking the potential of labour productivity within Algeria’s agricultural sector release the gates to an economically sustainable future? Or will the sector continue to be neglected and become the Achilles heel that cripples development? By addressing this question, we strive to shed light on the significance of labour productivity in shaping the path towards sustainable economic development in the Algerian economy. Using annual data from 1990–2021, this study employs an autoregressive distributed lag (ARDL) model with GDP/capita as the dependent variable, representing sustainable economic development and labour productivity indicators from Algeria’s agricultural sector as the independent variables. The scope of this research centers around two hypotheses: (1) a strong and positive long–run correlation exists between an increase in crucial labour productivity indicators in Algeria’s agricultural sector and sustainable economic development, as measured through indicators such as GDP per capita, and (2) in the short term, variations in The role of labour productivity within Algeria’s sustainable economic development . . . 95 labour productivity within Algeria’s agricultural sector are directly and positively correlated with changes in the nation’s GDP per capita, indicating the sector’s crucial role in the nation’s overall economic performance. In order to achieve the specified goal, the remainder of this study proceeds as follows. Section 2 establishes the background by briefly defining sustainable economic development and labour productivity. A review of pertinent literature is also provided, elucidating the research gap this study seeks to fill in Section 3 . Section 4 delineates the methodology employed, while results are detailed in Section 5 . Discussion is given in Section 6 , followed by a conclusion that offers recommendations based on the findings in Section 7 . 2. Sustainable economic development and labour productivity Economic growth is a fundamental concept in economic theory, with countries striving to achieve consistent GDP growth. Historically, technological progress and population growth were considered the primary factors driving economic growth (Pali´c et al.,2017). However, the continued rise in population and the constraints posed by limited natural resources and food supplies of transformed these factors into significant challenges (Jankovi´c Šoja and Bucalo Jeli´c,2016). To address these concerns, it has become imperative to strike a balance and reconcile the opposing forces. In this context, sustainable economic development has garnered considerable attention from researchers and policymakers. Sustainable development emerged as a strategy to balance economic growth, environmental protection, social equality, and the rational use of natural resources in the long term. However, the definition of sustainable economic development is complex and elusive. Frequently, precision is sacrificed for acceptance in attempting to describe the environmental, economic, and social characteristics of sustainable economic development. Sustainable development is a long–term approach to economic growth that considers environmental, social, and economic factors (Barbier,1998). The study of Bervidova (2002) has defined sustainable economic development as directly concerned with raising the material standard of living of people experiencing poverty, which can be quantified in terms of increased food and real income through providing interest in productivity in sectors such as agriculture that minimise resource depletion. Contrary to economic growth, sustainable economic development is based on increasing productivity and responsible use of resources (Brad et al.,2016). In contrast, labour productivity is a widely used concept in economics, its interpretation and measurement can vary depending on the specific context and methodologies employed (Bezat–Jarz˛ebowska and Rembisz,2016). At its core, labour productivity represents the ratio between output produced and labour inputs consumed in production. However, the complexity lies in how input and output are defined and quantified. Therefore, it is a baffling economic term (Dall’erba et al.,2005). Additionally, variations in labour productivity levels contribute to divergent growth rates among countries or regions Batóg et al (2009). Labour productivity refers to the quantity of output generated per unit of labour, with labour being quantifiable in either hours worked or the count of individuals employed (Deaconu et al.,2018). Within the agricultural sector specifically, standard productivity metrics incorporate measures of yield or value–added per agricultural worker, thereby quantifying sectoral output relative to labour input (Batóg and Batóg,2007). In other words, labour productivity is defined as output per unit of labor, where labour can be expressed as the number of hours worked, the number of individuals employed or the number of workers (Radło and 96 Zemri & Khetib Tomeczek,2022). Conversely, in the agricultural sector, labour productivity can be measured by the amount of agricultural output produced per unit of labour input, such as yield per agricultural worker or value added per agricultural worker. 3. Literature review Over the years, researchers and economists have conducted numerous studies to explore the intricate relationship between labour productivity and sustainable economic development. The existing literature presents various studies that dissect this complex relationship from various angles, each contributing unique insights and highlighting different aspects of this multifaceted topic. In research conducted by Gollin (2010) the correlation between labour productivity and sustained economic growth in developing nations from 1950 to 2010 has been examined. The author begins by discussing the importance of agriculture in developing countries, both in terms of its contribution to economic growth and its role in providing food security. This study examines theoretical arguments and empirical evidence supporting the hypothesis that enhancements in agricultural productivity have contributed to economic growth in developing countries. The author finds a strong positive correlation, suggesting that increasing labour productivity can promote economic development. Another study by Awan and Anum (2014) examined key determinants of agricultural productivity growth, and compared the effects of these factors on economic growth in a sample of seven selected nations in comparison to seven advanced countries. The researchers used a variety of econometric techniques, including time series analysis and a two–sector model, to study the economic dynamics of the variables. The study extensively analyzed multiple indicators of infrastructure, specifically focusing on the following variables: the percentage of employment in agriculture, labour productivity in the agricultural sector and aggregate labour productivity. The outcomes underscore a remarkable and positive link between labour productivity and economic growth in the context of Pakistan. The results underscore the importance of bolstering labour productivity as a driving force for promoting economic advancement. An additional study by Awan et al. (2015) focuses on the factors influencing rural women’s labour supply in agriculture, emphasising their potential contribution to economic development in the Rajanpur district of Pakistan. The study employs linear regression analysis and finds that women’s participation in the labour force can increase household income, reduce poverty, and contribute to economic development. While this study offers valuable insights, it is geographically confined to the Rajanpur district in Pakistan, limiting its generalizability to broader labour productivity issues. In research conducted by (Bezat–Jarz˛ebowska and Rembisz,2016), which sheds more light on factors affecting labour productivity, the study utilized a panel data model. Authors argue that enhancing efficiency can lead to increased agricultural output and productivity, which, in turn, can contribute to overall economic growth. This study offers a robust methodology, yet its approach, centered on the panel data model, might not fully capture the qualitative aspects of agricultural productivity, such as farmer well–being or environmental sustainability. In the study of Fedulova et al. (2019), the authors conducted a theoretical analysis of labour productivity in agricultural industries and its role in sustainable economic development. The primary goal of increasing worker productivity as the foundation of long–term economic development is considered. They argued that policymakers should focus on imple- The role of labour productivity within Algeria’s sustainable economic development . . . 97 menting measures aimed at encouraging farmers to adopt practices that increase agricultural productivity in order to achieve sustainable economic development. However, their theoretical analysis needs more empirical backing from diverse geographic contexts. Ibidunni et al. (2020) have emphasized the importance and significance of labour productivity in stimulating economic growth and development, namely within the agricultural industry of Sub–Saharan Africa. This study utilises a blend of data analysis and panel regression approaches to investigate the determinants of worker productivity in this specific location between 2010 and 2017. The study’s findings reveal substantial disparities in labour productivity levels and agriculture efficiency among the nations examined. The authors highlight many factors that influence worker productivity, such as infrastructure development and technology use. This research offers significant regional context, but it does not explicitly examine the example of Algeria. Additionally, some studies examine the labour productivity in the agricultural sector and its significance in Algeria. According to the study conducted by Laoubi and Yamao (2012), the agricultural sector in Algeria is confronted with several obstacles, such as diminished efficiency, elevated production expenses, and restricted market entry. The research recognizes the significance of agriculture in Algeria’s economy and its function in generating jobs, guaranteeing food security, and contributing to broader economic advancement. Nevertheless, this study needs empirical analysis and offers a full view of the many expressions of these difficulties. In their carefully designed study by Rey and Hazem (2020), conducted a meticulous analysis. They discovered that the agricultural sector in Algeria exhibits poor performance, making it one of the least productive sectors among Mediterranean nations. This article aims to assess the labour productivity in Algeria from 1984 to 2015, specifically in sectors like agriculture and hydrocarbons. The independent variable used for this estimation is the gross domestic product. The authors contend that Algeria should deliberate to foster the growth of its manufacturing and agricultural sectors. The study utilised gross domestic product GDP; however, GDP per capita is more effective in capturing the effects of labour productivity. Unlike the studies above, our study used GDP per capita as a measure, which offers a more detailed comprehension of the relationship between labour productivity and sustainable economic development. Although previous research offers valuable insights into the correlation between labour productivity and sustainable economic development, a gap exists in understanding this relationship within Algeria’s agricultural sector. Therefore, this study seeks to address this deficiency by utilising an ARDL model and offering policy suggestions grounded in facts to unleash the agricultural sector’s potential and contribute to Algeria’s sustainable economic development. 4. Data and research methodology The study employed the autoregressive distributed lags technique (ARDL) to analyze the impact of worker productivity in the agriculture sector on Algeria’s progress towards sustainable economic growth. The analysis included a span of 32 years, from 1990 to 2021. The use of this paradigm, initially devised by Pesaran and Smith (1998) and Pesaran et al. (2001). The ARDL model is well-known for its robustness when dealing with small sample numbers, making it a suitable choice for the 32–year study period. This characteristic guarantees accurate outcomes even when there are just a small number of observations. The ARDL model is particularly advantageous since it can include variables regardless of their integration order, 98 Zemri & Khetib whether they are I(0), I(1), or fractionally integrated (Pesaran et al.,2001). This feature is especially advantageous in our study since it enables the incorporation of variables such as GDP per capita, inflation, and others without requiring prior assessment of their integration order. The ARDL model can estimate both short-run and long-run parameters simultaneously, presenting a notable benefit (Jalil and Mahmud,2009). This feature is highly advantageous in the study as it aims to comprehend both the immediate short–term and enduring long–term effects of labour productivity on sustainable economic development. The dependent variable is gross domestic product per capita (GDP/capita). In contrast, the independent variables directly relate to labour productivity in the agricultural sector, including agricultural production, demographic changes, labour inputs, inflation, and agricultural labour productivity. All variables are measured as annual growth percentages, as shown in Table 1 . Time–series data for all variables were collected from economic surveys in Algeria, National Statistics Office in Algeria (ONS) and statistics through the Ministry of Agriculture and Rural Development, as well as data from the World Bank database World Development Indicators (WDI) and the Food and Agriculture Organization of the United Nations (FAO). Table 1. Dependent and independent variables used in the study Variable Description Measurement unit Source Dependent variable GDPcapita Gross domestic production per capita annual growth (%) WDI Independent varables GPVagri Gross production value in the agricultural sector annual growth (%) FAO POP Population of Algeria annual growth (%) ONS EMPagri Employed labour force in the agricultural sector annual growth (%) FAO INF Inflation in Algeria annual growth (%) VAWagri Value added per worker in the agricultural sector (constant prices in USD, 2015=100) annual growth (%) ONS GDP per capita annual growth percentage serves as a crucial outcome variable, offering a primary measure of economic output per individual and indicating the standard of living. This metric is particularly valuable in assessing sustainable development, as it reflects economic growth and the equitable distribution of economic gains. Enhancing this analysis involves considering several independent variables: The gross value of agricultural production, which highlights the agricultural sector’s productivity and economic contribution. Algeria’s population, to account for demographic impacts on agriculture and GDP. The employed labour force in agriculture, providing insights into labour productivity. Inflation rates, crucial for understanding fundamental economic change. The value added per agricultural worker, a key indicator of agricultural labour productivity. By incorporating these variables, the analysis can provide a more comprehensive understanding of Algeria’s economic growth and progress towards sustainable development. This approach examines the overall economic output and delves into the factors that drive this growth, offering insights into the efficiency and equity of the economic development process. The role of labour productivity within Algeria’s sustainable economic development . . . 99 Therefore, we were intrigued to examine the following research hypotheses: Hypothesis 1. There exists a strong and positive long-run correlation between increase in key indicators of labour productivity in Algeria’s agricultural sector and sustainable economic development, as measured through indicators such as GDP per capita. Hypothesis 2. In the short term, variations in labour productivity within Algeria’s agricultural sector are directly and positively correlated with changes in the nation’s GDP per capita, indicating the sector’s crucial role in the nation’s overall economic performance. Equation 1 aims to quantify the impact of agricultural gross production value, population dynamics, employment in agriculture, inflation, and value-added in agriculture on GDP per capita in Algeria. GDPcapita t=β0+β1GPVagri t+β2POPt+β3EMPagri t+β4INFt+β5VAWagri t+εt, (1) where β0is a constant term, while β1,β2,β3,β4and β5are the regression coefficients associated with each independent variable, representing the expected impact or influence on the GDP/capita. The error term εtin the model represents the unaccounted factors that are not explicitly included. A general equation in the autoregressive distributed lag (ARDL) framework can be derived as follows: GDPcapita t=γ0+ q ∑ i=1 γ1iGDPcapita t−i+ p ∑ j=0 γ2jGPVagri t−j+ p ∑ j=0 γ3jPOPt−j + p ∑ j=0 γ4jEMPagri t−j+ p ∑ j=0 γ5jINFt−j+ p ∑ j=0 γ6jVAWagri t−j+εt. (2) Equation 2 describes the ARDL model with qlags of dependent variable and plags of independent variables (not necessary the same number of time lags for each independent variable), which captures both the short–term and long–term relationship between them. Parameter γ0is a constant term, while γ1i,γ2j,γ3j,γ4j,γ5jand γ6jare the ARDL coefficients with respect to lagged variables on the right hand side. Upon estimating the ARDL model, the subsequent stage involves examining the long–run association between the dependent and independent variables through the utilization of the F–statistic test. The null hypothesis of the F–statistic test pertains to the coefficients on the lagged dependent variables (α1,α2, . . . , αk) are jointly equal to zero, indicating no long–run relationship.The alternative hypothesis suggests that at least one of these coefficients is not zero, indicating the existence of a long–run relationship. This is typically tested by asserting that the coefficient of the error correction term (ECMt−1) in the reparameterized ARDL equation is zero (H0:λ=0). Equation 3 illustrates the enduring, long–run relationship between the dependent and independent variables: ∆GDPcapita t=α0+ q−1 ∑ i=1 α1i∆GDPcapita t−i+ p−1 ∑ j=0 α2j∆GPVagri t−j+ p−1 ∑ j=0 α3j∆POPt−j + p−1 ∑ j=0 α4j∆EMPagri t−j+ p−1 ∑ j=0 α5j∆INFt−j+ p−1 ∑ j=0 α6j∆VAWagri t−j+λECMt−1+εt. (3) 100 Zemri & Khetib If the null hypothesis is rejected in favor of alternative (H1:λ=0) the long–run relationship exist. This suggests that the coefficient of the error correction term is significantly different from zero. 5. Results This section presents the results of the study on the economic variables affecting Algeria from 1990 to 2021. The analysis includes various statistical methods and econometric tests to understand the relationships between considered variables. Table 2 summarizes the descriptive statistics for the variables employed in the analysis, spanning 1990 to 2021. Table 2. Descriptive statistics of observed variables Variable Mean Std. Dev. Min Max Median GDPcapita 2.17 13.02 −28.06 23.98 0.89 GPVagri 3.37 9.14 −19.48 21.33 1.52 POP −0.06 5.09 −12.95 9.23 −0.78 EMPagri 1.81 3.25 1.36 2.53 1.86 INF −2.13 2.13 −9.00 1.10 −2.80 VAWagri 5.43 9.32 −17.95 30.43 4.36 The data exhibits substantial fluctuations in economic and demographic indices. The average GDP per capita, GPV in agriculture, and value–added in agriculture have all experienced a increase, whereas agricultural employment has declined. The inflation rates exhibit significant variation, whereas the population growth in Algeria remains generally steady. The ARDL bounds testing technique necessitates that variables possess an I(0) or I(1) integration order, so unit root tests should be utilized to ascertain the integration order. In the current investigation, we apply the Augmented Dickey–Fuller (ADF) test for this aim. Hence, we cannot comprehend the results of F statistics supplied by Pesaran et al. (2001) in the presence of variables integrated into I(2). The objective is to avoid obtaining misleading regression outcomes by ensuring that none of the variables are integrated at I(2) or higher levels. I(0) indicates that the variable is stationary at its level (no differencing required), while I(1) suggests that the variable requires first differencing to become stationary. Table 3. Unit root tests ADF results Test Critical values Oreder of statistic 1% 5% 10% integration GDPcapita −3.749 −3.716 −2.986 −2.624 I(0) GPVagri −4.650 −3.716 −2.986 −2.624 I(0) POP −4.788 −3.716 −2.986 −2.624 I(0) EMPagri −2.206 −3.709 −2.983 −2.623 I(1) INF −2.509 −3.716 −2.986 −2.624 I(1) VAWagri −3.686 −3.716 −2.986 −2.624 I(0) The Augmented Dickey–Fuller (ADF) test results in Table 3 suggest that gross domestic production per capita, inflation, value added per worker in the agricultural sector, and gross agricultural production are stationary. 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Agricultural Economics, 65(5):232–239. doi: 10.17221/199/2018agricecon 108 Zemri & Khetib Uloga produktivnosti rada u održivom gospodarskom razvoju: nalazi iz alžirskog poljoprivrednog sektora VRSTA ˇ CLANKA Prethodno priop´cenje INFORMACIJE O ˇ CLANKU Primljeno: 16. lipnja 2023. Prihva´ceno: 3. prosinca 2023. DOI: 10.62366/crebss.2023.2.002 JEL: C32, J24, O44, Q11 SAŽETAK Unatoˇc bogatim prirodnim resursima Alžira, postizanje održivog rasta te prosperiteta i dalje su izazovni. Usred toga, produktivnost rada unutar poljoprivrednog sektora stoji kao tihi ratnik, drže´ci u svom dohvatu tajne za pokretanje i unaprje ¯ denje alžirskog gospodarstva. Stoga ova studija nastoji otkriti kljuˇcnu ulogu produktivnosti rada u alžirskom poljoprivrednom sektoru kao svjetioniku održivog gospodarskog razvoja. Koriste´ci autoregresijski model s distribuiranim pomacima (ARDL) od 1990. do 2021. godine, rezultati otkrivaju da su bruto vrijednost poljoprivredne proizvodnje, inflacija i rast stanovništva znaˇcajne determinante BDP-a po glavi stanovnika u kratkom roku, dok je poljoprivredna dodana vrijednost po radniku tako ¯ der signifikantan dugoroˇcni pokretaˇc. Me ¯ dutim, zapošljavanje u poljoprivredi ima beznaˇcajan utjecaj, što ukazuje na smanjenje radne snage u tom sektoru i njihovo zanemarivanje posljednjih godina. Sveukupno, analiza potvr ¯ duje hipoteze o kratkoroˇcnim i dugoroˇcnim povezanostima izme ¯ du produktivnosti rada i održivog gospodarskog razvoja unutar alžirskog poljoprivrednog sektora. Ovi nalazi osvjetljavaju put koji sugerira da bi revitalizacija radne produktivnosti unutar alžirskog poljoprivrednog sektora mogla biti kljuˇcna poluga u transformaciji alžirskog gospodarskog krajolika prema prosperitetnijoj i održivoj budu´cnosti. KLJU ˇ CNE RIJE ˇ CI poljoprivredni sektor, Alžir, ARDL model, produktivnost rada, održivi gospodarski razvoj