Financial determinants of value based performance of construction firms in India

Abstract

PurposeThe purpose of the study is to examine the value-based performance of firms in construction sector in India using Tobin's Q and Market Capitalization (MCAP) and then determine their significant financial drivers.Design/methodology/approachThe study is based on data from 87 firms engaged in infrastructure, real estate, industrial construction and allied areas in India over a study period of 10 years. Three distinct forms of panel regression models have been developed using Tobin's Q and MCAP as dependent variables. The models developed are using Baltagi's (1981) Error Component 2SLS, Varadharajan-Krishnakumar's (1987) Generalized 2SLS and Arellano – Bower/Blundell – Bond's (1991) dynamic panel.FindingsThe study found that MCAP is a better suited value-based performance measure for construction sector firms in India. The study further reports that the age of the firm, profit after tax, investment in research and development, dividends, leverage and net fixed asset are significant positive drivers, whereas cash flow is a significant negative driver.Research limitations/implicationsThe study is limited to a geographic location; therefore, the findings of this study cannot be generalized.Practical implicationsAs MCAP is a better suited value-based performance measure of a firm in the construction sector, managers should focus on improving profitability, higher research and development activities, higher dividends and higher expenditures on net fixed assets for improvement.Originality/valueThis is an original attempt to examine the value-based performance of firms in the construction sector in India using Tobin's Q and MCAP.

Decoding a construction organisation's tendency to litigate: an understanding through financial statements

“…The panel does not contain any missing values and is strongly balanced. Considering the nature of the data (panel data), prior to subjecting the data to any regression analysis, the Unit Root test (using Levin's test for Stationarity), multicollinearity test (Variance Inflation Factor or VIF test) and heteroscedasticity test (Breusch–Pagan/Cook–Weisberg test) is performed (Singla and Prakash, 2023). On confirmation of the suitability of data, the Fixed Effect (FE) and Random Effect (RE) Generalized Least Squares (GLS) estimation (standard error and robust standard error) (Singla, 2019; Singla and Samanta, 2019) are applied, considering LCTE as the dependent variable and all other variables as independent and control variables as shown in Table 1.…”

“…Along these lines, a firm's age, size [represented by the Sales and Total Assets (Dang et al. , 2018)] and tangibility are considered (Eisenberg and Farber, 1997; Lederman, 1999; Bronsteen, 2009; Hylton and Lin, 2009; Singla and Samanta, 2019; Singla and Prakash, 2023).…”

“…Therefore, liquidity and cash flow parameters are to be extracted from the financial statements of construction firms. Operating cash flow (OCF) represents the cash flow efficiency (Singla and Samanta, 2019), and Current Ratio (CRTIMES, a ratio of Current Assets to Current Liabilities) represents short-term liquidity (Singla and Prakash, 2023), and therefore they are considered as frame-influencers (ratios are explained in Table 1). In an earlier attempt to understand the legal charges (Jagannathan et al, 2021) considered absolute values of financial variables.…”

“…In earlier studies dealing with the analysis of financial statements, the influence of a firm's size, age and financial tangibility are often considered key variables. Along these lines, a firm's age, size [represented by the Sales and Total Assets (Dang et al, 2018)] and tangibility are considered (Eisenberg and Farber, 1997;Lederman, 1999;Bronsteen, 2009;Hylton and Lin, 2009;Singla and Samanta, 2019;Singla and Prakash, 2023).…”

“…Considering the nature of the data, panel regression is performed on the consolidated financial data fetched from the database of the Centre for Monitoring Indian Economy (CMIE)-ProwessIQ. CMIE-ProwessIQ database is popularly used by researchers involved in quantitative studies on the financial data of firms in India (Singla and Prakash, 2023). The data for the year 2021 is incomplete in the database; therefore, consideration of the year 2021 in the analysis significantly shrinks the number of companies considered.…”