firms in standard databases. First, we sample all non-regulated US fir terjemahan - firms in standard databases. First, we sample all non-regulated US fir Bahasa Indonesia Bagaimana mengatakan

firms in standard databases. First,

firms in standard databases. First, we sample all non-regulated US firms with long-term debt between 1990 and 2006 from the Compustat database. Second, we fit a parsimonious logit regression with the dependent variable equal to one if the firm has an investment grade rating, and zero otherwise. The independent variables include the natural logarithm of firm size and earnings volatility (i.e.,standard deviation of ROA estimated over the years t, t-1,t-2, and t-3). Our in-sample predictions show that
the logit model has strong predictive power.Last, we apply the estimated coefficients to compute the probability of having an investment grade rating for each firm year observation in the global sample. We set the investment grade dummy (INVGRADE) equal to one if the estimated probability of an investment grade rating exceeds 50%, and zero otherwise.Our main variable of interest in Table 7 is the interaction between creditor rights and credit quality,CR X INVGRADE. As hypothesized, the estimated coefficient for
CR X INVGRADE(-0.32110) in Model 1 is negative and significant. We find a similarly negative and significant coefficient (-0.32402) in Model 2 after adding industry fixed affects to Model 1’s year fixed effects. These negative interaction terms mean that high credit quality reduces the impact of creditor rights on the propensity to pay
dividends.We perform a similar analysis for dividend amounts in Model 3 with year fixed effects and Model 4 with both year and industry fixed effects. The estimated
CR X INVGRADE coefficients (-0.00342 and-0.00343,respectively) are negative and significant. Consistent with expectations, credit quality acts as a mitigating factor in
the creditor rights-dividend payout relation
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firms in standard databases. First, we sample all non-regulated US firms with long-term debt between 1990 and 2006 from the Compustat database. Second, we fit a parsimonious logit regression with the dependent variable equal to one if the firm has an investment grade rating, and zero otherwise. The independent variables include the natural logarithm of firm size and earnings volatility (i.e.,standard deviation of ROA estimated over the years t, t-1,t-2, and t-3). Our in-sample predictions show thatthe logit model has strong predictive power.Last, we apply the estimated coefficients to compute the probability of having an investment grade rating for each firm year observation in the global sample. We set the investment grade dummy (INVGRADE) equal to one if the estimated probability of an investment grade rating exceeds 50%, and zero otherwise.Our main variable of interest in Table 7 is the interaction between creditor rights and credit quality,CR X INVGRADE. As hypothesized, the estimated coefficient forCR X INVGRADE(-0.32110) in Model 1 is negative and significant. We find a similarly negative and significant coefficient (-0.32402) in Model 2 after adding industry fixed affects to Model 1’s year fixed effects. These negative interaction terms mean that high credit quality reduces the impact of creditor rights on the propensity to paydividends.We perform a similar analysis for dividend amounts in Model 3 with year fixed effects and Model 4 with both year and industry fixed effects. The estimatedCR X INVGRADE coefficients (-0.00342 and-0.00343,respectively) are negative and significant. Consistent with expectations, credit quality acts as a mitigating factor inthe creditor rights-dividend payout relation
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perusahaan dalam database standar. Pertama, kita sampel semua perusahaan non-diatur AS dengan utang jangka panjang antara tahun 1990 dan 2006 dari database Compustat. Kedua, kita cocok dengan logit regresi pelit dengan variabel dependen sama dengan satu jika perusahaan memiliki rating investment grade, dan nol sebaliknya. Variabel independen meliputi logaritma natural dari ukuran perusahaan dan volatilitas laba (yaitu, standar deviasi ROA diperkirakan selama bertahun-tahun t, t-1, t-2, dan t-3). Di-sampel prediksi kami menunjukkan bahwa
model logit memiliki power.Last prediktif yang kuat, kami menerapkan koefisien diperkirakan untuk menghitung probabilitas memiliki rating investment grade untuk setiap observasi tahun perusahaan dalam sampel global. Kami mengatur boneka investment grade (INVGRADE) sama dengan satu jika probabilitas diperkirakan dari rating investment grade melebihi 50%, dan nol variabel utama otherwise.Our kepentingan dalam Tabel 7 adalah interaksi antara hak kreditur dan kualitas kredit, CR X INVGRADE . Sebagai hipotesis, koefisien diperkirakan untuk
CR X INVGRADE (-0,32110) di Model 1 adalah negatif dan signifikan. Kami menemukan koefisien sama negatif dan signifikan (-0,32402) di Model 2 setelah menambahkan industri tetap mempengaruhi ke Model tahun tetap efek 1 ini. Istilah-istilah ini interaksi negatif berarti bahwa kualitas kredit yang tinggi mengurangi dampak hak kreditur pada kecenderungan untuk membayar
dividends.We melakukan analisis yang sama untuk jumlah dividen Model 3 dengan efek tahun tetap dan Model 4 dengan kedua tahun dan efek industri tetap. Memperkirakan
koefisien CR X INVGRADE (-0,00342 dan-0,00343, masing-masing) yang negatif dan signifikan. Konsisten dengan harapan, kualitas kredit bertindak sebagai faktor yang meringankan dalam
kreditur hak-dividend payout hubungan
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