Operating performance Measures

Table 5-1 presents all the operating performance measures that have been employed for performance evaluation in IPO literature. It shows that ROA (Operating Returns on Assets) is the most commonly used performance measure in prior literature for judging operating performance (for example, Jain and Kini, 1994; Mikkelson et al., 1997; Kutsuna et al., 2002; Kim et al., 2004; Aharony et al., 2000; Huang and Song, 2003; Wang et al., 2001; Wang, 2005), followed by CFO (Cashflow From Operations on Assets), for example Jain and Kini (1994); Mikkelson et al. (1997); Kim et al. (2004); Aharony et al. (2000); Huang and Song (2003) and Wang et al. (2001).

Although most studies (Jain and Kini, 1994; Mikkelson et al., 1997; Huang and Song, 2003; Wang et al., 2001 and Wang, 2005) use EBITDA (Earnings before Interest, Tax, Depreciation and Amortisation) to proxy for corporate operating returns, some researchers (Kutsuna et al., 2002; Aharony et al., 2000 and Chen and Shih, 2004) adopt Net income (Earnings after Tax) and/or EBIT (Earnings before interest and Tax) to proxy for operating returns. I am in favour of EBITDA to proxy for operating returns, when a large multi-industry sample is examined. Tax calculation and depreciation policies vary from industry to industry, so that Net Incomes figures across the companies from different industry sectors may not be comparable with each other. In this sense, EBITDA is a better operating performance measure to compare some companies with others from different industries.

Furthermore, although most prior studies use asset-scaled measures and/or sale-scaled measures, some researchers (Kutsuna et al. 2002; Chen and Shih, 2004) also use actual earnings measures to examine the changes in operating performance. It is important to recognise that actual earnings figures may not as useful as asset-scaled figures to evaluate operating efficiency for IPO firms, because new capital is raised from the market and, as a result, the size of operations accordingly goes larger resulting from the IPO. So, actual earnings figures may not be appropriate to evaluate operating efficiency and profitability for IPO firms.

This research follows most of prior studies and adopts ROA (Operating Return, EBITDA, on lagged (-1) Assets) and CFO (Cashflow from Operations on lagged (-1) Assets) as the basic financial indicators forjudging corporate operating efficiency. The first reason to choose the two performance measures is that the two measures are widely employed as basic operating performance measures in financial statement analysis to evaluate firms’ operating efficiency; it is believed that ROA and CFO are good performance measures, particularly for evaluating a multi-industry sample of IPO firms. Secondly, the use of same performance measures is able to make my research more comparable to the findings in prior literature.

Besides the two basic indicators for performance evaluation, there are some other financial indicators to reflect corporate operating performance in different aspects. For example, sales and sales growth figures are often examined, since they may be useful to judge operating efficiency. Most prior IPO literature, such as Jain and Kini (1994); Kutsuna et al., (2002); Kim et al., (2004); Aharony et al., (2000); Huang and Song (2003); Wang et al., (2001); Chen and Shih (2004) and Wang (2005). examines IPO firms' operating scale and growth capability by studying sales and sales growth. This study will also investigate the sales and the sales grovrth for

Chinese IPO firms: (1) Sales denotes the size of operations. It is measured as ‘nominal sales’; alternatively, it can also be measured as ‘nominal sales scaled by lagged (-1) total assets’; (2) Sales growth is measured as the year-over-year growth rate of sales.

Table 5-2 lists all the operating performance measures adopted by this study, and a detailed definition is also provided for each of the performance measures. It should be noted that prior studies all use accounting performance measures, and none of previous studies uses economic profit measures, such as EVA (Economic Value Added) and so on. One of the possible reasons is that, according to China’s listing standards, accounting figures are the major performance measure to evaluate corporate operating performance, for example, qualifying for new securities offerings, IPO pricing and so on, and investors are primarily guided by accounting performance to assess the IPO firms’ operating results and management’s abilities. So, accounting performance is thus more relevant to IPO firms’ operating performance assessment. Based on this, Economic profit measure will not be adopted as the operating performance measures.

In order to control for the industry shocks, the IPO firms’ operating performance after industry adjustment will be examined. According to Mikkelson et al. (1997). industry-adjusted earnings numbers are obtained by deducting the median contemporaneous operating return of a group of industry-matched publicly traded firms. The matched firms are selected by matching the industry of the sample firms within the same sector of the CSRC’s Standard Industry Classification (SIC 2001). The CSRC’s SIC (2001) is currently the only official system, which is widely used and covers all the listed firms in mainland China. The structure of this classification follows western systems, such as the US SIC and the UK SIC, after being re-organised to make it more applicable to Chinese firms. Table 5-3 presents the Chinese SIC (2001) and sample distribution by industry sectors. According to the

SIC (2001), there are 13 specific industry sectors in total (from sector A to M), and sector C (Manufacturing) is further divided into 9 sub-sectors, as it is an extraordinarily large sector and covers too many companies (around 2/3 of total) Thus, in this study, sample companies are divided into these 21 industry (sub-)sectors, and matched publicly traded firms are those which come from the same industry sectors (or sub-sectors) and went public prior to 1998.