Impact of trade liberalisation on formal–informal interlinkages in India: does sectoral labour mobility matter?

Since a large mass of workforce in India is employed within informal segment of the economy,¹ enhancing income of the people engaged with this sector and bringing this sector out of poverty trap becomes crucial from a policy perspective (NCEUS 2007). It is argued that one way of reaching this goal is to attach this sector to the dynamic formal sector through linkages (Meagher 2013). Generally, informal sector is linked with formal sector either through vertical supply linkages by providing intermediate goods and services to the formal sector; or the informal sector operates independently by providing non-traded final goods and services meant for final consumption to the masses (Marjit and Maiti 2005:1). However, in the context of liberalised open economy, economic reforms, such as trade liberalisation, and deregulation of formal labour market, have transformed the inter-relationship between formal and informal sectors of the economy (Marjit and Maiti 2005). Empirical studies based on India show that trade openness and the consequent competitive pressure on Indian manufacturing bring about two forms of relation between formal–informal sectors due to the presence of wage rigidity in regulated formal labour market. These two forms are production outsourcing to informal sectors (e.g. Sundaram et al. 2012), and increasing trends of hiring contractual (informal) labour within formal sector² (e.g. Sen et al. 2010), respectively. Increasing pressure from international competition along with strict labour laws leads to adoption of flexibility in production organisation as a means of cost-cutting measures within formal enterprises in India, which allows formation of subcontracting relationship between formal–informal enterprises (Ramaswamy 1999; Mazumdar and Sarkar 2008; Siggel 2010). Recent findings reveal that the share of informal labour within formal (organised) sector has increased from 41% in 1999–2000 to around 48% during 2004–05, and further the figure reaches to 58% in 2011–12 (India Labour and Employment Report 2014: 31). Sundaram et al. (2012) argue that rigid labour laws in India disrupts the process of intra- and inter-sectoral labour mobility following trade liberalisation, which affects the formal sector to reap the benefit of trade liberalisation. However, no direct relation is established between the labour market flexibility, trade liberalisation and the consequent inter- and intra-sectoral labour mobility. Empirical evidence also shows that manufacturing growth could drive the growth of the informal services as well, due to trade liberalisation in India (Dehejia and Panagariya 2014). In Indian context, it is argued that benefits of economic reforms could be beneficial to a section of informal workforce engaged in high-income elastic informal services, such as construction, trade and transportations; and these growth-oriented informal services in turn absorb the labour from the low-productive sector such as agriculture, which ensures the overall growth of the economy (Kotwal et al. 2011:1156). Hence, the mobility of labour from low-productive to high-productive sectors is essential to ensure the overall growth of the Indian economy (Nayyar 2013: 165; Rada and von Arnim 2014:2). Sectoral labour mobility is critical for formal–informal sectors’ growth linkages since movement of labour within and between the sectors acts as a supply-side factor facilitating expansion of the sectors concerned, as the availability of cheap labour gives supply-side boost (Kar and Marjit 2001; Marjit 2003; Marjit and Kar 2009, 2011a). Besides, theoretical literature also, in the context of trade liberalisation and deregulation of formal labour market, depicts that mobility of labour between formal–informal sectors plays a crucial role in explaining growth linkages between these sectors of an economy (e.g. Agenor and Aizenman 1994; Marjit 2003; Marjit and Maiti 2005; Chaudhuri and Banerjee 2007, Marjit, Kar and Beladi 2007; Marjit and Kar 2009; 2011b).³However, lack of availability of longitudinal data on labour force survey in India deters us to analyse empirically the transmission mechanism of inter-sectoral labour mobility and its concomitant impact on the formal–informal linkages due to exogenous policy shock such as trade liberalisation. The present study explores whether and to what extent the degree of growth linkages between these two broad segments of the Indian economy varies with the varying degree of labour mobility across formal–informal sectors.

In the present analysis, Computable General Equilibrium (CGE) tool is used to capture the degree of labour mobility under assumed alternative labour market scenarios where segmentation in labour market is considered as one important binding constraint for expansion of the sectors.

In India, increasing occupational segmentation and information asymmetry hinders free mobility of labour; at the same time, social and cultural differences create segmentation in the labour market with imperfect labour mobility, which further constraints the evolution of common national labour market (Indian Labour and Employment Report 2014:35). Hence, there is a need for considering these aspects to conceptualise the labour market segmentation going beyond the formal–informal skill-specific segmentation in our analysis. ⁴

Present study has its own importance in relation to public policy in India with special reference to trade liberalisation in India. Trade liberalisation, as a part of economic reforms in India, was initiated during 1991 through various measures like easing of quantitative restrictions on imports and reduction in import duties across all the segments of the industry and agriculture. Although quantitative restrictions on all capital goods, consumer goods and agricultural products were phased out completely by 2001, process of reduction of tariff duty was relatively slow (Ahluwalia 2002). For instance, the weighted average tariff rate declined from 72.5% during 1991–92 to 24.5% during 1996–97, although with a significant upward revision in between years; and finally, it is proposed to be reduced by 15% in 2004 (Ahluwalia 2002: 4–5). Reduction of import duty through trade liberalisation becomes more crucial for last two decades due to India’s commitment to multilateral trade agreements in Uruguay Round of WTO; also at the bilateral level, India embarked on bringing down the import duty to zero on imports from Sri Lanka, Singapore, Korea, Japan, Malaysia, SAFTA and ASEAN countries (Banga and Das 2012a:X). Empirical evidence suggests that ease of import duty, abolition of import quota and licensing helped the growth of India’s export during 2000s due to the import of intermediate inputs at competitive prices by export-oriented firms (Banga and Das 2012a:1). However, external demand (export growth) did not ensure the overall growth of the Indian economy; it is rather domestic demand induced by gradual tariff liberalisation and the subsequent increase in competition in domestic market facilitated the growth of the economy (Banga and Das 2012b).

Lower tariff on final goods and inputs induced rising firm-level productivity of the Indian manufacturing, especially the import competitive industries and the industries where degree of regulation is relatively low (Topalova and Khandelwal 2011). Several other studies also support the view that trade liberalisation in India enhances the firm-level productivity of the formal sector firms (e.g. Krishna and Mitra 1998; Harrison et al. 2011). Albeit, other studies such as Pushpangadan et al. (2000) found no evidence of productivity growth of the formal sector due to trade liberalisation. On the contrary, empirical evidence shows that tariff liberalisation enhanced the average productivity of the informal firms in India which holds 80% of the manufacturing employment; however, this productivity augmentation occurred at the cost of the exit of least-productive informal firms from the industry (Nataraj 2011). Obviously, the question arises whether exit of the least efficient informal firms from the industry leads to reallocation of labour from low-productive informal firms to high-productive formal–informal firms/sector of the economy; otherwise, informal sector would experience an immiserizing growth (see, for example, Chakrabarti 2016). Hence, the degree of labour mobility becomes critical whilst examining the impact of tariff liberalisation on Indian manufacturing sector; and this becomes more relevant in the context of growth linkages between formal–informal sectors in India, since the latter sector is considered as the driving force of the former one to bring this sector out of poverty. In other words, the structure of the Indian labour market needs special focus whilst considering the impact of tariff liberalisation on interlinkages between formal–informal sectors in India. I envisage this issue in a counterfactual scenario analysis taking help of the CGE method, so that these scenarios could help in designing appropriate public policy to make growth inclusive.

Apart from wage employment, a large segment of population is engaged in informal self-employed activities in India; and thus, tariff reduction on traded goods (mostly formal sector’s goods and vast agricultural commodities) affects the earnings of the informal self-employed as well. According to the official statistics, the proportion of self-employed in Indian workforce has declined from 61% in 1972–73 to 52% in 2011–12 (India Labour and Employment Report 2014:31). However, the proportion of regular wage/salary earners, both formal and informal⁵ together, in the total workforce has increased marginally from 15.4% in 1972–73 to 17.9% during 2011–12; and around 65% of the regular wage/salary earners belong to organised (formal) sector which consists of production units of secondary and tertiary sectors of the economy (Indian Labour and Employment Report 2014:31). Within the unorganised sector, the composition of self-employed is 62% of total workforce followed by 31% casual labour and 7% regular labour (India Labour and Employment Report 2014:34). Hence, the impact of exogenous policy shocks on formal–informal interlinkages also determines the income of the informal self-employed as a substantial share of informal workforce is confined to the self-employed category.

I capture the income of the self-employed, both formal and informal, through the sources of households’ income. To assess the impact of exogenous policy shocks on the economy that consists of various entities, such as formal–informal activities, formal–informal households, government and rest of the world, I use Computable General Equilibrium (CGE) modelling technique based on the Social Accounting Matrix for India (SAM-India) for the year 2003–04. Although recent SAM for India is available for the year 2007–08; however, formal–informal disaggregation across sectors and various labour types are not provided in this SAM. On the contrary, I constructed the SAM for the year 2003–04 with the help of Input Output Transaction Table 2003–04 and disaggregated the SAM in terms of formal–informal activities and other relevant features specific to the research question using other supporting databases. The organisation of the study is as follows. First, Sect. 2 briefly explains the concept of segmented labour market and the notion of labour mobility that is applied in the scenario analysis. Second, Sect. 3 depicts the core structure of the CGE model, broadly in the line of PEP 1-1 model developed by Decaluwé et al. (2009); however, this model is tailored to the Indian scenario. Third, Sect. 4 describes briefly the Indian SAM used for the analysis. Model calibration, sensitivity analysis and simulation results are presented in Sect. 5, followed by conclusion in Sect. 6.

Segmentation in labour market arises either due to the skill specificity across various categories of labour (Agenor and Aizenman 1994) or due to the imposition of minimum wage leading to labour market rigidity in some segment of the labour force in the economy (Marjit and Kar 2009, 2011a). Whilst skill specificity restricts the movement of labour from low-productive to high-productive sectors; wage rigidity (due to the adherence to minimum wage) to a specific group of labour (formal regular labour in our case) may induce less mobility of labour (Corneliβen and Hubler 2005:5). However, skill acquisition could reduce the barriers to entry and facilitates sectoral labour mobility (e.g. see Marjit and Kar 2011b). Minimum wage legislation (mainly in formal sector) does not necessarily ensure compliance across the board; it is found that the degree of minimum wage compliance varies across enterprises and between permanent and contractual workers in India (ILO 2018: 86); also, minimum wage legislation does not ensure that it would reach to the low-paid workers (Murgai and Ravallion 2005). As it is true that labour market segmentation can be defined in terms of permanent and contractual workers, imposition of minimum wage through collective bargaining by formal regular labour gives rise to another form of segmentation in the labour market as the casual labour in formal sector may sometime left out of the coverage. Hence, the level of governance (or lack of implementation of common minimum wage) is the defining characteristic of broader labour market segmentation in India.⁶ Keeping this view in mind, I consider two forms of labour market conditions in this study: segmented labour market and absence of segmentation in the labour market. Within segmented labour market framework, I allow separately wage rigidity (in absence of skill specificity) and skill specificity (in absence of wage rigidity) at the sectoral level; whilst absence of segmentation (i.e. absence of wage rigidity and skill specificity) is also considered assuming perfect inter-sectoral mobility of informal labour as a separate scenario.

One important point to note that the constructed base SAM reflects the inherent existence of segmentation of Indian labour market, where absence of mobility of formal regular labour is considered from formal to informal sectors; this is done primarily due to the lack of statistical evidence showing mobility of formal regular labour from formal to informal sector; and hence, this labour type is not linked with informal sector in the SAM. However, growing phenomenon of informalisation within formal sector in India results in the mobility of the informal labour to formal activities; and this is captured in the base SAM. Hence, absence of segmentation in our counterfactual scenario also implies the free mobility of informal labour from informal sectors to formal sectors, given the inherent structural segmentation within Indian labour market. Free mobility leads to competition between informal and formal labour for getting absorbed within expanding formal sectors. On the contrary, skill specificity at the sectoral level depicts the absence of mobility of formal sector-specific labour to other formal sectors; however, informal labour is fully mobile.

In this section, I explained the CGE model with specific features, and the key variables, that are compatible to the Indian scenario; however, the overall model is the replica of PEP 1–1 model developed by Decaluwé et al. (2009) with minor modification. It is assumed that both formal and informal sector production function of an output is a nested function, as depicted in the standard neo-classical CGE model (e.g. see Decaluwé et al. 2009): at the top level sectoral output is a fixed-coefficients Leontief production function of value-added and aggregate intermediate consumption; at the bottom level value added of a sectoral output is a constant elasticity of substitution (CES) production function of composite labour and capital/land (in case of agricultural production). In my constructed SAM, formal–informal sectors, including agricultural sector, produce intermediate goods and services and all the sectors are interlinked (both intra- as well as inter-sectoral) through forward and backward production linkages. Hence, informal sector produces intermediates for the formal sector and vice versa. Technically speaking, aggregate intermediate demand for a sector’s output (formal or informal) is captured through Leontief production function of individual input demand from each activity (formal and informal). Hence, no substitution is possible in case of consumption of intermediate input demand. Only the possibility of substitution arises at the top level where various types of labour are imperfectly substitute to each other. Hence, the source of flexibility in informal sector, which provides intermediate goods and services to formal sector, emerges from the substitution between the informal regular and casual labour.⁷

In this study, composite labour has three categories: formal regular labour, informal regular and casual labour; however, both land and capital are sector-specific. Throughout the analysis, I considered that capital is immobile across sectors. It is hardly accepted notion in the context of developing economies that capital is mobile across sectors; it is rather assumed that sectoral capital stock is fixed within a short-period of analysis (Robinson 1989:908). Further, Robinson (1989):910 argues that so far as developing economies are concerned, the vast segment of agriculture and service sectors uses quite different kinds of capital goods as compared to manufacturing sector. Hence, it is a plausible assumption to consider capital is sector-specific in the model.⁸ No distinction is made between land and capital used in agricultural production. So land is also considered as specific factor used in agricultural production. Land is not mobile; hence, each agricultural activity uses specific type of land with certain agro-ecological conditions that is unique for each type of crop (Wong 2012). These are the standard features suitable in India scenario. Informal (non-agricultural) sector’s output is non-traded; on the contrary, both agricultural and formal sector’s products are traded. Hence, agricultural and formal sector products face competition in both domestic and foreign markets. Aggregate output is expressed in terms of constant elasticity of transformation aggregation function between domestic supply and export. India is considered as the small country and hence, formal sector and agricultural produce are supplied infinitely at the exogenously given world price of export in this CGE model. Demand for domestically produced imports competing goods and services, and their imported counterparts are imperfectly substitute and follow Armington function. There are 13-household class depicted in my constructed India-SAM and there are three sources of households’ income: labour income, capital (or land) income and transfer income received from Government and rest of the world as remittances. Consumption demand function of the households follows Linear Expenditure System. Gross domestic product (GDP) at basic and market prices are calculated based on the base-level SAM data.

Macroeconomic closures that are used in the model are as follows. In external sector, current account balance is allowed to vary with the fixed real exchange rate. For government closure, government savings is flexible, whilst tax rates imposed on households’ income and enterprise income are considered as fixed. Also government expenditure on goods and services is considered as exogenous. In savings-investment front, investment is savings driven. Change in stock (i.e. inventory accumulation or decumulation) is exogenous in our model.

Base-level India-SAM is constructed for the year 2003–04 based on Input Output Transaction Table (IOTT) provided by Central Statistical Office, Government of India. However, methodology of constructing SAM is beyond the purview of this article. India-SAM consists of 18 formal–informal production activities, which are food crops sector, cash crops sector, horticulture crops sector, agro-allied and resource-based sector (AGALD); formal and informal segment of food and beverages (FodBvrF and FodBvrI); formal and informal counterpart of textiles and wearing apparel (TextF and TextI); agro-based formal (AGROMF) and informal sectors (AGROMI), excluding food and beverages and textiles and wearing apparel; non-agro-based manufacturing products, excluding capital goods sector (NAGF and NAGMI respectively for formal–informal counterpart); formal and informal capital goods sector (CAPMF and CAPINF respectively); infrastructure services, including construction for both formal and informal counterpart (INFRF and INFRI); and finally, formal–informal other services (OTSRF and OTSRI). Agro-allied and resource-based activities (AGALD) is the combined entity of three broad sectors specified in the initial constructed SAM, which are animal husbandry, forestry-logging and fishing, i.e. agriculture and allied activities; and mining and quarrying activities, i.e. other primary sectors’ activity as termed as resource in our constructed SAM. Apart from formal–informal classification of food and beverages, and textiles’ (including wearing apparel) industries, three other agro-based industries such as tobacco products, wood products and leather products are merged into one category of other agro-based manufacturing activities with their respective formal–informal segmentation (AGROMF and AGROMI). Primary reason of identifying food and beverages and textiles as separate activities rather than including in the aggregative agro-based industries is due to the fact these are the two sectors where majority of informal (or unorganised) manufacturing activities are confined. According to the unorganised manufacturing survey conducted by National Sample Survey Office (NSSO), Government of India, during 2005–06, 49% of the entire manufacturing activities are dominated by textiles (including wearing apparel) and food and beverages’ products (NSSO 2007:21). Manufacturing of paper and printing products, chemical and allied products, metal products and miscellaneous manufacturing products are further grouped under non-agro-based manufacturing products, excluding capital goods sector (NAGF and NAGMI respectively for formal–informal counterpart). Electrical and non-electrical, including transportation equipment are clustered together under the capital goods-producing sector separately for formal and informal counterpart (CAPMF and CAPINF). Infrastructure services and construction activities are further aggregated under the broad heading of formal–informal infrastructure services (INFRF and INFRI) in my aggregate SAM. Finally, under the heading of other services, we merge both other services and trading services specified in my disaggregate SAM. There are 13-household classes in the SAM, which are rural marginal and small agricultural self-employed household (MSA-HH); rural medium and large agricultural self-employed household (MLA-HH); rural agricultural labour household (AL-HH); formal capitalist household (Cap-HH); rural own account household (ROA-HH); rural establishment household (REstb-HH); urban own account household (UOA-HH); urban establishment household (UEstb-HH); rural formal wage labour household (RFWL-HH); rural informal wage labour household (RIWL-HH); urban formal regular wage labour (UFrWL-HH); urban informal regular wage labour (UIrWL-HH) and urban informal casual wage labour household (UIcWL-HH).

The simulation results are obtained based on the CGE model depicted above with specific rigidities in capital and land market. Model calibration is performed using the values of elasticity parameters obtained from other studies. Besides, most of the parameters are estimated endogenously from the base-level SAM. Goldar et al. (2013) estimate the elasticity of substitution (EOS) between labour and capital across Indian manufacturing industries using CES production function. To keep the parity with the aggregate sectors specified in the SAM, I compute the average values of the relevant elasticities by combining the corresponding industries under aggregate industrial sectors. Further, the similar procedure is followed to obtain the elasticity of substitution across agricultural activities and various services. Information on elasticity values of the agriculture and services is collected from Pradhan and Sahoo (2008). However, equal elasticity values are assigned across formal and informal segments of the respective sectors. Appendix: Tables 15, 16 provides respectively the EOS across various sectors and other associated parametric values. For sensitivity analysis I perform the simulation by imposing three values of elasticity of substitution amongst three categories of labour: casual labour, informal regular labour and formal regular labour. This will help to capture the representative firm’s degree of substitutability of various categories of labour due to changing relative wages.

Under the segmented labour market assumption, I consider that nominal wage rate in formal regular labour market is fixed and institutionally determined by bargaining. Hence, nominal wage does not respond due to changing labour demand and labour supply; Keynesian involuntary unemployment in formal regular labour market exists in the model in few cases.⁹ It is noteworthy that the model does not depict the explicit role of trade union, such as wage bargaining process and the decisive role of trade union during recession to withhold the retrenched formal labour. In CGE model absolute values of commodity and factor prices are determined in terms of model numéraire. Since nominal wage is fixed with respect to model numéraire which is domestic consumer price index (CPI) in our model, it is equivalent to fixing the real wages; further, the nominal wage is implicitly indexed to consumer price index (Boeters and Savard 2011: 52–53). Fixing real wage in formal regular labour market characterises the labour market rigidities, which gives rise to involuntary unemployment. On the contrary, wage in informal labour market is considered as market determined with full-employment condition prevails in both categories of informal labour market (i.e. regular and casual). This is indeed an appropriate assumption of full employment in informal labour market on the ground that informal labour, for survival, get absorbed in some activity; or in other words, they cannot stay unemployed without doing any activity although it might be insignificant and under-remunerative (Marjit 2003; Marjit and Kar 2011a:4).

At the initial scenario analysis which is termed as segmented labour market-1, I consider the segmented labour market with respect to wage rigidity in formal regular labour market along with full mobility of informal labour from formal to informal sectors and perfect mobility of formal regular labour within the formal sub-sectors.¹⁰ This is particularly important in the present scenario of Indian labour market where regular labours in formal sectors are protected by minimum wage legislation and the formal labour market is segmented. Although wage fixation comes through collective bargaining by labour union (regular labour in formal sector in our case) which ensures minimum wage amongst permanent/regular labour; it does not necessarily ensure in case of casual/contractual labour employed in formal sector. This is the question of the degree of governance. I accommodated this aspect of governance in the CGE analysis through the defining characteristics of segmented labour market-1; where wage rate of the formal regular labourer is fixed rather than market determined, contrary to the case of informal regular and casual labour where wages are market determined, irrespective of their origin of employment (formal/informal). In the analysis of second scenario of segmented labour market, which is termed as segmented labour market-2, I impose a condition of labour immobility from formal capital goods sector to other formal sub-sectors due to skill specificity of this category of labour at sectoral level.¹¹ However, in this model wage rate in formal regular labour market is not fixed; wage rate is allowed to be determined according to the force of demand–supply in labour market. Skill specificity is one important aspect that creates large differences in endowments amongst labourers and in this respect labour is not considered as homogeneous. In the analysis of third scenario, I assume absence of segmentation in labour market; however, full employment prevails across three categories of labour market; only wage rate is allowed to clear the market.

In all the scenario analyses, I consider differential wage rates across three categories of labour at the base category; and the wage rates are assumed in descending order respectively for formal regular labour, informal regular labour and casual labour. This is done to reflect the observed wage differential across said categories of labour in India where formal regular labour receives relatively higher wage than contractual casual and informal labour. For example, in 2004–05 regular workers received an average daily wage of Rs. 307 as compared to casual workers at Rs. 99 (Indian Labour and Employment Report 2014: 96). To introduce the wage differentials, I normalise the wage rate of informal casual labour to unity at the baseline level and then I increase the baseline value of informal regular wage rate by 10 percentage point from the initial value of casual labour and 20 percentage increment is assigned to the wage of formal regular labour with respect to the baseline value of informal casual labour wage rate.¹²

I summarise below the scenario analysis under alternative labour market settings undertaken in this study.

Scenario-A1: 50% tariff cut on imported goods under segmented labour market-1 (full mobility of informal labour) settings;

Scenario-A2: 50% tariff cut on imported goods under no segmentation of labour market settings;

Scenario-A3: 50% tariff cut on imported goods under segmented labour market-2 (partial mobility of formal labour but full mobility of informal labour) settings;

Each scenario analysis is performed with respect to three different values of CES elasticity of substitution of composite labour parameter of each activity/sector (\(\sigma_{j}^{LD}\)). The values of the elasticity parameter are considered as 0.2, 1.2 and 2.5, respectively. However, these values are chosen on ad-hoc basis. These values are taken to undertake the sensitivity analysis. Empirical estimates show the elasticity of substitution (EOS) between workers with different skills (where skill is reflected on difference in educational attainment) varies between 1.5 and 2 (Wingender 2015: 272). However, Wingender’s estimates show that although EOS is fixed at 1.5 in non-agricultural sector, the values are specified as 2.25 and 3 in case of agricultural sector in two different scenarios (Wingender 2015: Table 2). I assumed the above-mentioned three values of composite labour elasticity keeping in mind the skill specificity of each category of labour, notably formal–informal regular labour and casual labour. It is noteworthy that there are no studies in India that empirically estimate the elasticity values. Hence, the values I chose reflect three cases of mobility, namely rigid, moderate and flexible across all the sectors of the economy.

This study reveals that labour mobility based on the extent of labour market segmentation gives rise to varied outcomes in terms of linkages between formal–informal sectors under tariff reduction; and also, the degree of expansion amongst the growing non-agricultural sectors, both formal and informal, varies. The study found a one-to-one correspondence between the growth of the similar activities that belong to formal and informal segments of the economy due to introduction of unilateral tariff reduction under both the scenarios of segmented labour market-1 and absence of labour market segmentation. The study also found that absence of labour market segmentation (i.e. absence of wage rigidity and skill specificity) with full mobility of labour gives rise to relatively higher growth in expanding formal sector activities vis-à-vis the growth of the similar activities under segmented labour market with full mobility of labour. In case of informal sector, output growth is lower when labour market is not segmented as compared to segmented labour market. However, the growth of the expanding informal activities is further worsened due to the restriction imposed on labour mobility from capital goods industry as it reflects skill specificity; however, restricted labour mobility has highest impact on the expansion of the formal activities. Hence, the study argues that the nature of labour mobility, which depends on the structure of the labour market, has differential implication on the growth of the formal–informal sectors in India in the backdrop of trade liberalisation. This study has profound implication in relation to public policy. Cost of labour market adjustment due to trade shock is assessed by analysing changing functional income distribution across households. This study also found dwindling functional income distribution across informal non-agricultural households under both the initial scenarios irrespective of the nature of labour mobility. Although skill specificity in capital goods sector improves the functional income distribution across all the types of informal households, the functional income distribution of formal wage labour households goes down further. The findings of the study emphasise on designing appropriate social welfare schemes by the government to support specific groups of the households as a part of compensation due to introduction of structural policy through trade liberalisation.