fects the existence of any account activity in the current month; Bille risti t-1 is a dummy variable that reflects the existence of a bill with a non-zero balance in the previous balance Utili t. for utilization. is debt divided by the credit limit: Eit is an error term. Table 1 provides the regression results Figure 1 plots the expected frequency of fees as a function of account tenure, holding the other control variables fixed at their means. This analysis shows that fee payments are fairly common when accounts are initially opened, but that the frequency of fee payments declines rapidly as account tenure increases. In the first four years of account tenure, the monthly frequency of cash advance fees drops from 57% of all accounts to 13% of all accounts The frequency of late payment fees drops from 36% to 8%. Finally, the frequency of over limit fees drops from 17% to 5% To establish that the estimated pattern is robust to alternative specifications, we estimate several variants. We estimate equation 1 as a conditional logit; the results are qualitatively similar. We also repeat the analysis controlling for behavior and FICO scores, both lagged by three months to reflect the fact that they are only computed quarterly. The coefficients on the spline of tenure are almost unchanged. Finally, to eliminate the possibility that attrition from the sample has distorted the results, we have tried restricting the sample te only those account present for all 36 months; the results are little changed It is also of interest to know how the amount of fees paid vary by account tenure. For the late fee and over limit fees. the fee amount is constant, while for the cash advance fee the fee amount can vary over time. Figure 2 reports the average value of each fee type as a function of account tenure, conditional on other factors that might affect fee payment. The data plotted in Figure 2 is generated by estimating Vit =a+oi+vtime SplineTenure t) +n, Purchase t +n2 Activei. t n3 bille risti t-l +1Util;t-1+∈;t The dependent variable Vit is the value of fees of type j paid by account i at tenure t. All other variables are as before. Table 2 reports the regression results II Tenure in all figures starts at month two since borrowers cannot, by definition, pay late fees or over limit fees in the first month their accounts are opflects the existence of any account activity in the current month; −1 is a dummy variable that reflects the existence of a bill with a non-zero balance in the previous balance;  , for utilization, is debt divided by the credit limit;  is an error term. Table 1 provides the regression results. Figure 1 plots the expected frequency of fees as a function of account tenure, holding the other control variables fixed at their means.11 This analysis shows that fee payments are fairly common when accounts are initially opened, but that the frequency of fee payments declines rapidly as account tenure increases. In the first four years of account tenure, the monthly frequency of cash advance fees drops from 57% of all accounts to 13% of all accounts. The frequency of late payment fees drops from 36% to 8%. Finally, the frequency of over limit fees drops from 17% to 5%. To establish that the estimated pattern is robust to alternative specifications, we estimate several variants. We estimate equation 1 as a conditional logit; the results are qualitatively similar. We also repeat the analysis controlling for behavior and FICO scores, both lagged by three months to reflect the fact that they are only computed quarterly. The coefficients on the spline of tenure are almost unchanged. Finally, to eliminate the possibility that attrition from the sample has distorted the results, we have tried restricting the sample to only those account present for all 36 months; the results are little changed. It is also of interest to know how the amount of fees paid vary by account tenure. For the late fee and over limit fees, the fee amount is constant, while for the cash advance fee, the fee amount can vary over time. Figure 2 reports the average value of each fee type as a function of account tenure, conditional on other factors that might affect fee payment. The data plotted in Figure 2 is generated by estimating,   (2)  =  +  +  + ( ) +1  + 2 + 3−1 +1 −1 +  The dependent variable    is the value of fees of type  paid by account  at tenure . All other variables are as before. Table 2 reports the regression results. 11Tenure in all figures starts at month two since borrowers cannot, by definition, pay late fees or over limit fees in the first month their accounts are open. 7