“Does management of working capital enhance firm value? Empirical analysis of manufacturing enterprises in India”

The long-term financial health of a corporation is assessed by its capacity to meet short-term financial commitments. Optimum working capital that maximizes enterprise value varies across companies. The purpose of this paper is to investigate whether Indian manufacturing enterprises’ firm values are influenced by working capital management efficiency. The data are taken from 2016 to 2022 (a seven-year period) for 223 top BSE-listed manufacturing companies. Firm value (explained variable) is proxied using Tobin’s Q, and the constituents of working capital, which include the net trade cycle, inventory period, debtors’ collection period, and creditor payment period, are taken as explanatory variables. The study also controls for any differences in firm characteristics and economic conditions by employing firm size, age, current ratio, net profit ratio, sale growth and GDP growth rate. Balanced-panel data analysis is conducted by employing a two-step generalized method of moment technique. Net trade cycle, inventory period and debtors’ collection period are found to have a strong and significant positive impact on Tobin’s Q. The findings however did not report any evidence of the significant relationship between creditor payment period and Tobin’s Q. Additionally, the outcomes also evidenced that firm value is positively impacted by company size, net profit ratio, sales growth and GDP, whereas negatively affected by firm age. This paper suggests that manufacturing firms may potentially enhance their firm value by prolonging the net trade cycle, period of inventory and lengthening the credit period to customers till the level of attainment of an optimum working capital.


INTRODUCTION
All the financial decisions taken by corporations are centered towards increasing the performance and value of shareholders that is being depicted in the stock market price. Working capital management (WCM), as highlighted by Sharma and Kumar (2011), is an essential corporate finance theory that addresses funding of investment in current assets. Working capital is essential to meet operational expenses and support sales growth and expansion efforts. It represents the excess of short-term assets over short-term liabilities. Expressed differently, the part of long-term capital used for investment into current assets is called net-working capital.
Managerial effectiveness can improvise WCM efficiency (Prasad et al., 2019). On the one hand, a corporation needs sufficient liquidity to guarantee payment of its short-term debts and maintain a steady flow of revenue from profitable ventures (Abuzayed, 2012). Concentrating solely on liquidity, on the other hand, diminishes a firm's profitability (Smith, 1980). Efficient WCM involves making important financial decisions to allow the companies to cover its operation-related expenses and other short-term financial obligations as they occur and ensuring that funds are not blocked in current assets thereby balancing profitability with liquidity (Shin & Soenen, 1998).
As pointed out by Smith and Gallinger (1988), WCM addresses the difficulties linked to effective administration of short-term nature assets, namely, cash, debtors, and inventory and short-term liabilities like creditors and focuses on issues that arise in balancing these elements. WCM policies varying from stringent to liberal may have opposing effects on the financial liquidity and profitability of corporations. A liberal inventory policy may increase the carrying cost, whereas a stringent inventory policy would increase the ordering cost besides leading to stock-out situations. Likewise, a liberal credit policy towards customers may result in a boost in sales and hence increase profits, besides; it may lead to a larger amount of bad debts and affect earnings quality. Greater liquidity in the form of cash can save short-term financing cost but at the same time might compromise on long-term profitable and value creating investments, which ultimately hampers the adequate returns to shareholders. Moreover, delayed payment to suppliers may allow the cash to be used for financing other operational expenses hence saving on short-term financing costs; conversely, it could turn out to be expensive as the possible cash discounts would be lost. Lazaridis and Tryfonidis (2006) suggest that WCM inefficiency could lead to failures of start-ups and corporate organizations. As a result, financial managers address this conundrum by maintaining optimal amounts of working capital and its various components (Nazir & Afza, 2009).
As per Sartoris and Hill (198), regardless of the significance of interrelationships between different working capital constituents, empirical literatures on the plausible effect on corporate performance by WCM constituents (Kim & Chung, 1990;Schiff & Lieber, 1974) are few particularly in developing economies like India. Moreover, two opposing conceptions have been witnessed in research over the years on the degree of capital allocation in working capital. One perspective suggests that maintaining higher levels of working capital can assist businesses in expanding sales and obtaining increased discounts for early payments, thereby potentially raising the value of firms. Trade credit leads to an increase in sales and better customer relationships. Maintaining higher levels of inventory shall ensure regular stock supply, avoid stock out situations besides securing against price fluctuations. Besides, short-term sources for financing working capital can offer lower interest rates and are not exposed to the risk of inflation (Mahmood et al., 2019

LITERATURE REVIEW AND HYPOTHESES
Working capital management has three main aspects. First being the positioning perspective that is generated from the current ratio analysis using balance sheet figures. According to Richards and Laughlin (1980), the second dimension is assessed on operational cycle efficiency, quantified by using Cash Conversion Cycle (CCC). Third, being comparison of long-term financing to short-term financing, highlighting the key distinctions between the two. WCM is crucial to a firm's val-ue and performance (Smith & Begemann, 1997;Smith, 1980 Besides, a group of control variables were also employed to account for variations in company characteristics. Following Samiloglu and Demirgunes (2008), firm size (SIZE) has been measured through logarithm of total assets. Since the per-formance of an enterprise is impacted by its stage of the life cycle in which it operates, aging of firms (AGE) has been controlled in the analysis. Debtequity ratio is proxied to cover leverage (LEV). Percentage change in revenue from year to year measures a firm's growth (GROW). Current ratio (CR) is used to measure liquidity. The profitability of a company is ascertained by net profit ratio (NPR).
Year-on-year growth rate in GDP (GDP) is taken as an exogenous variable to account for the macroeconomic effect.
Panel data regression techniques have been applied to estimate the models. Baltagi (2005) highlights numerous advantages offered by panel data, including substantial volume of data observations; reduced collinearity among exogenous variables; increased degrees of freedom and enhanced monitoring for individual heterogeneity. Before estimating the models, diagnostics tests have been performed to check for and minimize any biases in the estimated values. Pooled Ordinary Least Square (OLS) method has been applied for diagnostic testing to ascertain any evidence of multicollinearity, heteroskedasticity and endogeneity. Variance Inflation Factor (VIF) assessing the presence of multicollinearity is presented in Table 2.
All the independent variables' VIF values were found to be below 1.54, indicating that the model is not affected by multicollinearity. Presence on unit root was checked through the Levin-Lin-Chu test. The data was found to be stationary since the null hypotheses were rejected for all variables. The White test has been used to determine whether heteroskedasticity is present. The null hypothesis stands rejected which confirms that the data Where models 1, 2, 3 and 4 test hypotheses 1, 2, 3 and 4, respectively. Table 3 presents descriptive statistics. The composite sample of 223 firms across a 7 year-period makes an aggregate of 1,561 firm-year observations.

RESULTS
The calculated average value of TQ is 3.32192, and lowermost value is 0.044672, and the uppermost The study employed Pearson's correlation coefficient to assess intensity of the linear relationship between explained, explanatory and control variables. Appendix 1 presents correlation matrix. TQ is positively correlated with NTC (at 1%). Additionally, TQ is also significantly positively related with IP, DCP and CPP. Further firm size, working capital ratio, net profit margin, and GDP growth rate show a significant positive relation with TQ. A firm's age and leverage are found to be negatively correlated with TQ but the relationship is insignificant.
Other independent variables do not have strong linear relationships with one another; the correlation coefficients for their relationships are below 0.40. The correlation coefficient between NTC and IP is 0.77, confirming a significant positive association. Likewise, the positive association between NTC and DCP is 0.56, also statistically significant and positive. Conversely, the association coefficient between NTC and CPP is -0.1039, which is statistically significant but negative, supports working capital theory. This will not create a multicollinearity problem as these variables do not appear together in one model.

The empirical findings of 2-Step Generalized
Methods of Moments (white cross section robust covariance matrices) studying the impact of WCM components respectively on TQ are shown in Table 4. Using the Arellano-Bond test, no serial order correlation was found. Sargan statistics further confirm the validity of instruments used. Thus, the requirements of GMM were satisfied. The coefficients of lagged TQ 1-t show a statistically significant (at 1% level) negative connection with the current TQ for all four models. At a 5% significance level, NTC exhibits a favorable impact on TQ. The study therefore accepts H1. The findings align with the previous studies executed by Sharma and Kumar (2011) and Moussa (2018). This means that the stock market investors tend to assign higher value on firms having longer NTC since those firms have potential to create higher returns on their investments. The research findings are, however, contradictory to the previous study conducted in India by Sawarni et al. (2021) where an inverse relationship is reported between NTC or CCC and firm value.
Model 1 was re-estimated using other WCM components, i.e., IP, DCP and CPP (model 2, 3 and 4, respectively), to determine the robustness of the findings (see Table 4). The study uses GMM estimators to re-estimate models 2, 3 and 4. P-value of Sargan statistics further supports the reliability of GMM estimators, indicating validity of instruments used. Results from the applied Arellano-Bond test found no problem of serial correlation. The IP positively affected TQ at the 1% significance level, which postulates that a higher inventory period increases company value. The empirical outcomes also reveal a positive influence of DCP on , showing that better profitability and growth in sales result in greater firm value. Firm size is strongly and positively associated with the TQ confirming the earlier outcomes of Anton (2016), Aggrawal and Padhan (2017), and Samourna and Romavati (2020). Moreover, the outcomes indicate a notable and adverse impact of a company's age on TQ across all models. CR and leverage of a firm, however, are not found to be significantly related with firm value.

DISCUSSION
The empirical findings present a significant positive influence of NTC on firm value, indicating that investors, in the emerging market of India, value firms with longer NTC. This finding is similar to those of Abuzayed (2012) and Moussa (2018).    Note: T-values are in parentheses, *** significant at 5%, ** significant at 1%.
A possible explanation to this relationship can be attributed to the fact that in less developed economies, financial markets are not developed and hence fail to penalize managers for inefficient working capital management. IP and DCP are found to positively significantly influence firm value. This implies that having a lengthier net trade cycle by having a longer inventory period and providing extended credit period to customers contribute to increase the value of Indian manufacturing companies. Having a larger inventory period increases the earnings by lowering the ordering cost, reducing possibilities of stock-out situations and that larger inventory does not necessarily imply reduction in sales. Moreover, extended credit period to customers helps achieve larger sales and thereby improving the profitability and company's market value. Due to the superiority of products and services offered by foreign companies compared to those of Indian companies, the latter are compelled to provide extended credit terms to maintain their presence in the market and effectively counter the competition (Sharma & Kumar, 2011 With respect to the impact of control variables on firm value, growth in sales is found to exhibit a positive effect on firm value, which reflects that an increase in growth opportunities contributes to better market value of companies. Similar re-sults are shown by Bhatia and Srivastava (2016) and Moussa (2018). GDP growth rate having a positive association with firm value can be understood by the fact that with fall in GDP levels, companies typically have low market value, and vice versa. Besides, the study also confirms that a company's market value increases with the increase in its profitability. According to Endri and Fathony (2020), companies with high profitability attract more investment from investors in a company's share thereby increasing firm value. Additionally, GMM estimates indicate that the enterprise value is positively and significantly influenced by its size, reflecting that larger firms with better working capital management tend to maximize value for their shareholders (Hirdinis, 2019; Anton, 2016; Aggrawal & Padhan, 2017). Companies with substantial total assets are deemed to possess favorable outlooks and the capacity to generate profits, distinguishing them from enterprises with lesser total assets hence better valued by the investors. The findings are similar to those of Deloof (2003) and Mathuva (2010). Moussa (2018), Gupta (2018) and Gupta (2017), however, found a negative relationship between firm size and firm value. The study further reveals an inverse relationship between the age of firms and Tobin's Q. This means that older firms tend to perform less as compared to younger firms. Even though age could mean gaining more experience, this is a characteristic of the disadvantage that comes with passage of time. Age in this way is interpreted as obsolescence, which Drucker (1987) argues is regenerative and endangers sustainable development. The idea of the organizational life cycle is therefore associated with the age of a firm (Cole, 2002).

CONCLUSION
This study examines the effect of working capital efficiency on firm value of Indian manufacturing firms listed in S&P BSE 500 Index. The study developed four models to explore the impact of the working capital efficiency components, i.e. net trade cycle, period of inventory, debtors' collection period and creditor payment period each, on firm value measured through Tobin's Q. Hypotheses 1, 2, 3 and 4 state that net trade cycle, inventory period, debtors' collection period and creditor payment period, respectively, have a significant impact on Tobin's Q (each hypothesis corresponding to model 1, 2, 3 and 4, respectively). Data for the seven-year period from 2016 to 2022 were collected for 223 firms. The study utilized a two-step GMM estimator to analyze a balanced panel data set comprising 1,561 firm-year observations. The model also controlled for firm specific characteristics and economic conditions by using firm age, firm size, current ratio, net profit margin, leverage, growth in sales and GDP growth rate as control variables. The outcomes of the regression analysis confirm a significant positive effect of net trade cycle, period of inventory and debtors' collection period on Tobin's Q. Therefore, the study accepts hypotheses 1, 2 and 3. The study, however, found no significant correlation between creditor payment schedule and firm value, and hence hypothesis 4 is rejected. Besides, firm value is positively impacted by an increase in size, net profit margin, growth in sales and growth in GDP and negatively influenced by firm age.
The empirical analysis reveals that manufacturing firms in India can enhance their enterprise value by extending the net trade cycle, implementing a strategy that involves maintaining elevated inventory levels and extending credit period to customers. The results of this study are inconsistent with previously conducted studies in India and in other countries that report a negative relationship between working capital efficiency and firm value. It is therefore suggested to make further investigations by future researchers by conducting comparative studies across countries besides longitudinal and cross-section research. The current study only controlled for firm specific and economic factors. Future studies can extend the research by controlling for financial constraints and corporate governance mechanisms. The reported results can be helpful to managers in maintaining the optimum level of raw materials and inventory, devising appropriate credit policies, and maintaining optimum net trade cycle.