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Table 2: Variable definitions and theoretical justifications

 

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Table 2, Part 1: The performance equation, EQ1

Variable name

Definition, theoretical justification and data source

Pi,t

Performance

A generic abbreviation for the financial performance measured at time t for firm i. One of the following two specific measures is applied: a market-to-book ratio and a standard measure of the return on total assets see below.

MTBi,t

Market-to-book ratio

MTB is measured by: , where TotDebt is total debt defined as all interest-bearing and capitalized-lease obligations, or the sum of long- and short-term debt. MarkCap is market capitalization and Assets are total assets as defined below.I More details in Chapter 5, Section 5.1. Get dissertation. Data source: Worldscope-Piranhaweb.

RonAi,t

Return on assets

For industrials it is calculated as (Net Income before Preferred Dividends + ((Interest Expense on Debt - Interest Capitalized) * (1-Tax Rate))) / Last Year's Total Assets * 100. For financials it is different. For instance, for banks it is (Net Income before Preferred Dividends + ((Interest Expense on Debt - Interest Capitalized) * (1-Tax Rate))) / (Last Year's Total Assets - Last Year's Customer Liabilities on Acceptances) * 100.I More details in Chapter 5, Section 3.1. Get dissertation. Data source: Worldscope-Piranhaweb.

OWPi,t,d

Piecewise managerial ownership

Ownership is measured either by total ownership by all officers and directors or by insider ownership. The measurement details are described below in this table, Part 2. To account for a possible non-linear relation both of these ownership measures have been transformed using a piecewise linear function with the ownership intervals: [0;0.5%], [0.5;1%], [1;5%], [5;30%], and [30;100%]. More details about this specification follow below this table. As an explanatory variable in the performance equation it is intended to confirm one of the following two hypotheses: The natural selection argument (Hypothesis 5) or the combined incentive entrenchment argument by Morck et al. (Hypothesis 3) as explained in Chapter 2, Section 2.3 and Section 2.5. Get dissertation.

LnSALPi,t,c

Log of manager salary

A generic abbreviation for the natural logarithm of managerial compensation measured at time t for firm i. One of the following two specific measures is applied: annual salary by the sum of the two highest paid officers and annual salary by the sum of the two highest paid directors (see below). In both cases the measure includes the dollar value of fixed salary, bonuses, stock options and other perquisites.

LnOFFSALPi,t,c

Sum of salary for the two highest paid officers million $

This is the annual salary or remuneration of the companyís officers as reported in the proxy statement at time t for firm i.IV Specifically, LnOFFSALP is measured as the natural logarithm of the sum of the salary of the two highest paid officers. Furthermore, to account for non-linearities this measure is split by a piecewise linear function measuring the salary in the ranges from 0 to 1 million dollars, from 1 to 6 million dollars and from 6 million dollars and above. More details below this table. It is hypothesized that financial performance increases by increasing officer compensation for low levels of compensation, but decreases for high levels. This scenario could be explained by the argument that firms with higher officer compensation are more likely to attract the most capable and dedicated people. However, at very high levels of compensation the officer becomes too rich too quickly to care about continuing to work hard to keep his/her job. Data source: SEC-Piranhaweb.

LnDIRSALPi,t,c

Sum of salary for the two highest paid directors million $

This is the annual salary or remuneration of the companyís directors as reported in the proxy statement at time t for firm i.IV Specifically, LnDirSALP is measured as the natural logarithm of the sum of the salary of the two highest paid officers. Also, this measure is split by a piecewise linear function in the ranges from 0 to 1/2 million dollars, from 1/2 to 3 million dollars and from 3 million dollars and above. More details below this table. The associated hypothesis should be similar to those that apply for officer salary, although the cut-point of the piecewise linear functions are expected to be lower than for officer salary because directors typically are paid less and work less than full time. Data source: SEC-Piranhaweb.

DSALi,t

Salary dummy

This is a dummy equal to one whenever the observation of managerial salary (officer or director) is missing and zero otherwise. In regressions where this dummy is used, the salary observations have been completed by adding the 25% quantile salary whenever the salary observations are missing. The 25% value was selected because it is believed to be a reasonably good approximation of the true values of the missing observations. The coefficient to DSAL should be insignificant to support the hypothesis that firms with substituted values are no different in terms of performance than other firms.

Assetsi,t

Total assets

Assets are total assets. For industrials it is measured the standard way. For financials it is measured differently. For instance, for banks it is the sum of cash, total investments, premium balance receivables, investments in unconsolidated subsidiaries, net property, plant and equipment and other assets.I Data source: Worldscope-Piranhaweb.

LTDebti,t

Long-term debt

Long-term debt is used for the measurement of the firmís leverage by dividing it by total assets. Total assets are defined above and long-term debt represents all interest bearing financial obligations, excluding amounts due within one year.I Leverage is included in EQ1 because it is believed to be a potentially important governance structure like ownership. Furthermore, the squared leverage is included to identify possible optimal capital structures. In particular, a significant negative coefficient of the leverage and a significantly positive coefficient of the squared leverage could be reasoned by an argument saying that firms with strong financial performance prefer not to borrow and firms with high debt levels may perform better because it provides high-powered incentives. More details follow below this table. Data source: Worldscope-Piranhaweb.

MarkCapi,t

Market capitalization

MarkCap is the year end market capitalization of all outstanding shares all types included.I The size variable is used as a control variable in most studies of performance and it enters EQ1 using a logarithmic transformation: LN(MarkCapi,t). It is hypothesized to be positively correlated with performance. When performance is measured by the market-to-book ratio the positive correlation could be reasoned by a liquidity premium for large firms. Independent of applied performance measure a positive correlation could be reasoned by at least two other stories: 1) a survivor bias stating that exceptionally well performing firms in general grow faster and therefore are larger; 2) monopoly pricing stating that large firms in general are more able to earn monopoly profits than small firms; and 3) earnings volatility stating that small firms in general are less diversified than large firms and therefore more often are turning out negative earnings. Data source: Worldscope-Piranhaweb.

BETAi,t

Stock market beta

This is the standard measure of market risk as described in Chapter 5, Section 4. Beta is based on between 23 and 35 consecutive month-end price percent changes relative to a local market index.I Beta is included in EQ1 to control for differences in financial performance that are the result of differences in beta. In particular, high beta firms should deliver higher performance to compensate investors for higher levels of non-diversifiable risk. More details below this table. Data source: Worldscope-Piranhaweb.

PPECapi,t

Total property plant and equipment net

Total property plant and equipment net represents total gross property, plant and equipment less accumulated reserves for depreciation, depletion and amortization. Total property, plant and equipment gross represents tangible assets with an expected useful life of over one year, which are expected to be used to produce goods for sale or for distribution of services.I Data source: Worldscope-Piranhaweb.

CapExpi,t

Capital expenditure

This is the capital expenditure from the cash flow statement. It represents the funds used to acquire fixed assets other than those associated with acquisitions.I Capital expenditure divided by total property, plant and equipment (see above) is used in EQ1 to explain performance. One could argue that higher capital expenditures to property, plant and equipment should be associated with higher performance because such firms either are more willing to undertake longer term investments and / or are more capable or positioned to initiate profitable investment projects. Alternatively, if capital expenditures are associated with depreciations that are higher than can be justified economically, then the total asset values of firms with high capital expenditures will be lower than they should be. This situation would create a measurement bias for the applied market-to-book ratio (MTB) that would result in a positive relation between MTB and CapExp to PPECap. However, this bias is unclear with regard to return on assets because it affects both assets and earnings downwards. Data source: Worldscope-Piranhaweb.

Salesi,t

Net sales or revenues represent gross sales and other operating revenue less discounts, returns and allowances.I Data source: Worldscope-Piranhaweb.

OpeInci,t

Operating income

This is operating income after depreciation. It represents the difference between sales and total operating expenses.I When divided by sales (see above) it measures the profit or income per unit of sales. Ceteris paribus higher profit rates should be associated by higher financial performance. However, this is not the same as regressing financial performance on financial performance (which would be absurd) because the profit rate is only one of two basic components of financial performance that also need to account for the capital used to create this profit. Data source: Worldscope-Piranhaweb.

R&Di,t

Research & development costs

Research and development expense represents all direct and indirect costs related to the creation and development of new processes, techniques, applications and products with commercial possibilities.I Although the primary source was Worldscope, this item was collected from three databases in order to boost the number of observations. More details below in Table 3, Part 2. Get dissertation. When divided by total assets it measures the R&D intensity of the firm. If performance is measured by q as defined above, a high R&D ratio should also be associated by a high q because R&D intensive firms do not capitalize R&D expenses on their balance sheet. However, it could also be hypothesized that firms with higher R&D rates perform better because they are more foresighted and have more potential for profitable inventions. Data source: Worldscope/Extel/SEC-Piranhaweb.

DR&Di,t

R&D dummy

This is a dummy equal to one whenever the observation of R&D is missing and zero otherwise. In regressions where this dummy is used, the R&D observations have been completed by entering zero whenever R&D is missing. The coefficient to DR&D should be insignificant to support the hypothesis that firms with substituted values are no different in terms of performance than other firms.

Adveri,t

Marketing costs

The marketing or advertising costs include expenses for postage, telephone, PR and other similar marketing expenses as well as expenses in connection with the publication of the annual and interim reports. This item was collected from the Extel database.V When divided by total assets it measures the advertising intensity of the firm. If performance is measured by q as defined above, a high advertising ratio should also be associated by a high q, because advertising intensive firms do not capitalize advertising expenses on their balance sheet. However, perhaps it could also be hypothesized that firms with higher marketing rates perform better because they are able to sell more at higher prices than other firms. Data source: Extel-Piranhaweb.

DAdveri,t

Marketing dummy

This is a dummy equal to one whenever the observation of Adver is missing and zero otherwise. In regressions where this dummy is used, the Adver observations have been completed by entering zero whenever Adver is missing. The coefficient to DAdver should be insignificant to support the hypothesis that firms with substituted values are no different in terms of performance than other firms.

DIndust1i,t

Three-digit industry dummies

This is three-digit industry dummies created from a four digit SIC code. The classification contains (119-1) dummies. It is hypothesized that performance is highly determined by the type of industries either because some industries actually perform better at certain times but also because industry-specific accounting practices that biases the measurement of performance. Data source: SEC-Piranhaweb.

DExchangei,t

Stock exchange dummy

This is a dummy for the stock exchange (or primary stock exchange) that the firm belongs to. The classification contains (5-1) dummies. In particular, the New York Stock Exchange, NASDAC National, NASDAC International, American Stock Exchange or a category of other US stock exchanges.IV It is only applicable for the full sample. Such dummies are hypothesized to be important determinants of performance as a result of the different codes of conduct that each exchange has implemented. Data source: SEC-Piranhaweb.

DIncorpi,t

Dummy for country of incorporation

A new category of dummies fixing the country of incorporation. Seven dummies (7-1) were created covering the following locations: USA, Canada, Latin-America, Tax-Shelter-Countries, Angle-Europe, Continental Europe, and Asia. These dummies are believed to be important determinants for both ownership and performance because of differences in the legal environment from country to country.IV Data source: SEC-Piranhaweb.