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49. CEO is a dummy, where 1 signiÞes that the executive is a CEO in a given Þrm year. Size is assets at the beginning of the year, winsorized at 1%. Industry Þxed effects are at the 2-digit SIC level. Note that I cannot estimate the model with a more disaggregated Þxed effect (e.g., at the level of the Þrm or the executive) because my measure of product differentiation does not vary across executives in a given Þrm or over the time span of data in the sample. Data is annual for 1993-2004, with only manufacturing (SIC 2000-3999) Þrms included. Standard errors are robust to heteroskedasticity and arbitrary serial correlation within industry-year cells.
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50. Following Doraszelski and Satterthwaite (2003), we assume that scrap values are randomly drawn from a distribution F () with E (φi) = φ, independently and identically distributed across Þrms and periods, and privately observed prior to making exit and effort decisions. We let χi (ω, φi) ∈ {0, 1} indicate exit or continuation respectively. With respect to our earlier deÞnition in Section 2, the symmetric MPE now comprises also an operating probability, which for an incumbent is given by ϕi (ω) = R χi (ω, φi) dF (φi) and represents the probability that incumbent i remains in the industry, while for a potential entrant is ϕe i (ω) = R χe i (ω, φe i ) dF (φe i ) and represents the probability that potential entrant i enters the industry.
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51. High-tech is a dummy variable, where 1 signiÞes that the Þrm is from one of the high-tech industry deÞned by Loughran and Ritter (2004). Percentage Owned is the percentage of common equity held by the executive through stocks and options. Industry Þxed effects are at the 2-digit SIC level. Note that I cannot estimate the model with a more disaggregated Þxed effect (e.g., at the level of the Þrm or the executive) because my measure of product differentiation does not vary across executives in a given Þrm or over the time span of data in the sample. Data is annual for 1993-2004, with only manufacturing (SIC 2000-3999) Þrms included. Standard errors are robust to heteroskedasticity and arbitrary serial correlation within industry-year cells.
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52. Industry Þxed effects are at the 2-digit SIC level. Note that I cannot estimate the model with a more disaggregated Þxed effect (e.g., at the level of the Þrm or the executive) because my measure of product differentiation does not vary across executives in a given Þrm or over the time span of data in the sample. Data is annual for 1993-2004, with only manufacturing (SIC 2000-3999) Þrms included. Standard errors are robust to heteroskedasticity and arbitrary serial correlation within industry-year cells.
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53. Note that I cannot estimate the model with a more disaggregated Þxed effect (e.g., at the level of the Þrm or the executive) because my measure of product differentiation does not vary across executives in a given Þrm or over the time span of data in the sample. Data is annual for 1993-2004, with only manufacturing (SIC 2000-3999) Þrms included. Standard errors are robust to heteroskedasticity and arbitrary serial correlation within industry-year cells. The sample is limited to include only executives that were a CEO in a given Þrm year.
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54. Performance is deÞned as the product of the total inßation-adjusted return to shareholders and the beginning of period market value of the Þrm divided by 100 (Jensen and Murphy (1990)). Industry is deÞned by four-digit SIC code. Position is the ratio of the Þrm’s sales to industry median sales in the beginning of the year, winsorized at 1%. Product differentiation is a dummy variable, where 1 signiÞes that the industry is classiÞed as one with differential products according to Rauch (1999). Industry concentration is domestic four-Þrm concentration ratio.
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55. Performance is deÞned as the product of the total inßation-adjusted return to shareholders and the beginning of period market value of the Þrm divided by 100 (Jensen and Murphy (1990)). Industry is deÞned by four-digit SIC code. Position is the ratio of the Þrm’s sales to industry median sales in the beginning of the year, winsorized at 1%. Product differentiation is a dummy variable, where 1 signiÞes that the industry is classiÞed as one with differential products according to Rauch (1999). Industry concentration is domestic four-Þrm concentration ratio. Size is assets at the beginning of the year, winsorized at 1%. Industry Þxed effects are at the 2-digit SIC level.
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56. Performance is deÞned as the product of the total inßation-adjusted return to shareholders and the beginning of period market value of the Þrm divided by 100 (Jensen and Murphy (1990)). Product Uniqueness is deÞned as selling expense scaled by sales (Titman (1989)). Industry is deÞned by four-digit SIC code. Product differentiation is a dummy variable, where 1 signiÞes that the industry is classiÞed as one with differential products according to Rauch (1999). Industry concentration is domestic four-Þrm concentration ratio. CEO is a dummy, where 1 signiÞes that the executive is a CEO in a given Þrm year. Size is assets at the beginning of the year, winsorized at 1%.
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