Employment Effects of Import Competition on Agro-Based Manufacturing Firms in Nigeria

The unit root properties of the variables were tested using the Augmented Dickey-Fuller (ADF) test, specified as follows: (1) Δγt=Xtβ+δγt−1+αi∑i−1pΔγt−i+εt \Delta {\gamma _t} = {X_t}\beta + \delta {\gamma _{t - 1}} + {\alpha _i}\mathop \sum \nolimits_{i - 1}^p \Delta {\gamma _{t - i}} + {\varepsilon _t} Where:

∆ – Difference operator

Before assessing the impact of import competition on agro-based manufacturing employment in Nigeria, it is essential to first estimate the level of import competition. Following Ngwudiobu et al. (2018), the ratio of imports to domestic demand was used as a proxy for import competition. This study employed econometric modelling of labour demand to examine the effects of import competition on employment in agro-based manufacturing industries. The employment equation is derived from the theoretical labour demand function by Trivedi and Alexander (1988) and is expressed as: (2) L=L(W/PN, PT/PN, KT, KN) L = L\left( {W/{P_N},{P_T}/{P_N},{K_T},{K_N}} \right) Where:

W/P – real exchange rate,

Labour demand equations at the industry level were estimated by regressing employment against various explanatory variables, which were derived from conventional labour demand theory (Tuhin, 2015). The labour demand function (3), following Ngwudiobu et al. (2018), was transformed into an estimable equation, with some modifications informed by the structure of Nigeria’s labour market, specifically for manufacturing employment. The model is represented as: (3) logEMPt=α0+α1logEMPt−1+α2logIMCOMt++α3logEXCOMt+α4logKt−1+α5logRUCCt−i++α6logRUCLt−i+α7logTOt+α8logGEt++α9logINFt+εt \begin{array}{*{20}{c}} {{\rm{log}}EM{P_t} = {\alpha _0} + {\alpha _1}{\rm{log}}EM{P_{t - 1}} + {\alpha _2}{\rm{log}}IMCO{M_t} + }\\ { + {\alpha _3}{\rm{log}}EXCO{M_t} + {\alpha _4}{\rm{log}}{K_{t - 1}} + {\alpha _5}{\rm{log}}RUC{C_{t - i}} + }\\ { + {\alpha _6}{\rm{log}}RUC{L_{t - i}} + {\alpha _7}{\rm{log}}T{O_t} + {\alpha _8}{\rm{log}}G{E_t} + }\\ { + {\alpha _9}{\rm{log}}IN{F_t} + {\varepsilon _t}} \end{array} Where:

EMP_t – employment in the agro-based industry at time t

The second labour model, used to investigate the effect of the terms of trade on agro-based manufacturing employment, is represented as: (4) logEMPt=α0+α1logEMPt−1+α2logTOTt++α3logTRADEt+α4logGDPt+α5logLOANt++α6logEXRt+εt {\rm{}}\begin{array}{*{20}{c}} {{\rm{log}}EM{P_t} = {\alpha _0} + {\alpha _1}{\rm{log}}EM{P_{t - 1}} + {\alpha _2}{\rm{log}}TO{T_t} + }\\ { + {\alpha _3}{\rm{log}}TRAD{E_t} + {\alpha _4}{\rm{log}}GD{P_t} + {\alpha _5}{\rm{log}}LOA{N_t} + }\\ { + {\alpha _6}{\rm{log}}EX{R_t} + {\varepsilon _t}} \end{array} Where:

EMP_t – Employment in the agro-based industry at time t

Figure 1 illustrates employment trends (measured in millions of workers per year) in the agro-based manufacturing sector versus other manufacturing sectors from 1986 to 2021, following the introduction of the Structural Adjustment Programme (SAP). Initially, employment in agro-based manufacturing surged, surpassing other manufacturing sectors due to strong demand for agricultural products. However, between 1991 and 2002, employment in the sector declined, driven by an exchange rate crisis, neglect of the agricultural sector, and the residual effects of the oil boom. These factors led to reduced investment and labour demand in agrobased manufacturing firms, allowing other manufacturing sectors to employ more workers during this period.

Between 2002 and 2004, employment in both agrobased and other manufacturing sectors rose sharply, with agro-based manufacturing leading in workforce expansion. From 2004 to 2010, employment levels stabilised, with agro-based manufacturing maintaining a higher share of workers. Although the sector experienced a slight dip in 2011, employment rebounded between 2012 and 2013.

From 2014 to 2016, employment in other manufacturing sectors showed an upward trend, while agrobased manufacturing remained stable but retained its lead in workforce size. Both sectors faced a decline in 2017, but agro-based manufacturing recovered between 2018 and 2021, likely supported by government interventions aimed at revitalising the agricultural sector.

Overall, agro-based manufacturing consistently employed more workers than other manufacturing sectors, highlighting its significant contribution to Nigeria’s labour market.

Table 2 shows the impact of various factors on employment in Nigeria’s agro-based manufacturing sector. The regression analysis reveals that import competition, export competition, real unit cost of labour, trade openness, and inflation all significantly influence sector employment. Import competition, in particular, has a significant negative effect on agro-based manufacturing sector employment at the 5% significance level (Author et al., 2013; Dauth et al., 2014). This suggests that increased import competition leads to reduced employment, limiting labour force participation and suppressing wages in local markets.

This finding is consistent with previous studies, such as Author et al. (2013), which found that rising import competition led to higher unemployment in the US manufacturing sector. Similarly, studies by Akkuş (2014), Balsvik et al. (2015), Blanco et al. (2020), and Citino and Linarello, (2021) have shown that import competition negatively affects employment in both developed and developing countries.

In contrast, export competition has a positive and significant effect on agro-based manufacturing sector employment. This suggests that increased export competition boosts production, which, in turn, drives employment growth. This finding aligns with research by Akkuş (2014) and Dauth et al. (2021), who found that export demand and competition led to increased labour demand in the manufacturing industries of Turkey and Germany, respectively.

Capital stock also has a positive and significant impact on agro-based manufacturing employment, suggesting that an increase in capital stock leads to higher employment (Arestis et al., 2007). This indicates that capital and labour are complementary inputs in the sector. Conversely, the real unit cost of capital negatively impacts employment, suggesting that higher capital costs reduce job availability. This occurs because increased capital costs reduce the revenue available for salaries, thereby decreasing the demand for employment (Byoun et al., 2022).

The real cost of labour similarly has a negative and significant impact on employment in the agro-based manufacturing sector. Higher labour costs, when not accompanied by increased demand or production, reduce the industry revenue available for labour, thereby lowering labour demand. As noted by Bildirici (2004) and Byoun et al. (2022), high labour costs can increase unemployment rates. Firms may respond by reducing labour costs or laying off workers, ultimately reducing employment (Byoun et al., 2022; Agrawal and Matsa, 2013; Benmelech et al., 2019; Benmelech et al., 2021; Chodorow-Reich, 2014; Duygan-Bump et al., 2015).

Trade openness also has a negative and significant effect on employment in the agro-based manufacturing sector (Pierce and Schott, 2016; Liu et al., 2022). Increased trade openness results in higher competition from imported goods, which reduces the demand for locally produced agro-based products, leading to decreased employment (Kpognon et al., 2020; Asaleye et al., 2017; Onifade et al., 2019). While some studies have reported mixed results (Hasan et al., 2011), the majority suggest that trade openness harms employment in various countries, including Nigeria.

Inflation, however, has a positive and significant impact on employment in the agro-based manufacturing sector. This suggests that rising inflation leads to higher employment in the sector, as increased prices stimulate demand for products, prompting higher production and, consequently, a need for more labour. This supports the expectation that rising inflation can reduce unemployment, with higher employment rates boosting consumers’ purchasing power, which in turn drives demand for goods and services. A similar finding was reported by Orji et al. (2015) in their study on the relationship between unemployment and inflation in Nigeria, where they found a significant positive relationship between these two variables.

Table 3 shows that terms of trade, trade changes, GDP, and exchange rates significantly impacted employment in Nigeria’s agro-based manufacturing sector. Specifically, the terms of trade had a positive and significant effect on employment, suggesting that improved terms of trade increase employment. This finding aligns with Onifade et al. (2019), who found that a 1% improvement in the terms of trade could reduce unemployment by 0.35%, as favourable terms of trade signal a strong manufacturing-based economy.

Trade changes also had a positive and significant influence on agro-based manufacturing employment, implying that increased export demand or exportation boosts industry output and employment (Dauth et al., 2017). Additionally, GDP positively affected employment, indicating that economic growth drives demand for goods and services, thereby increasing labour demand in the agro-based manufacturing sector.

These results align with the International Monetary Fund’s position that rising GDP is likely to increase employment but contradict Ani et al. (2019), who found that GDP positively influences unemployment in Nigeria. Conversely, the exchange rate had a negative and significant impact on agro-based manufacturing employment, suggesting that an increase in the exchange rate reduces employment. This occurs because exchange rate devaluation discourages exports, leading to reduced production and labour demand in the sector. This finding supports Ani et al. (2019), who found that the exchange rate negatively impacts employment in Nigeria, but contradicts Bakhshi and Ebrahimi (2019), who concluded that the exchange rate reduces unemployment in Iran.