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					  An empirical investigation of auditor
     independence and accounting
  conservatism: Further evidence from
    Taiwan market-based incentives

Authors: Yi-Hsing Liao
                          Outline Presented
              Research motivation
              Research purposes
              Research design
                Hypotheses development
                Empirical methodology and variable measurement
                Sample formation and data resources
              Empirical results and analysis
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              Summary and concluding remarks
                              Research motivation
                According to the literatures surveyed, whether non-audit
             services really create a threat to auditor’s independence and
             reporting quality has been controversial for a long time and not
             yet come to a conclusion currently. In addition, a number of prior
             studies find that they are short of significant evidence to support
             the argument that non-audit services reduce auditor
             independence. One of the reasons why the auditing literatures can
             not draw a consistent conclusion on the matter is that they only
             focus on the impacts of non-audit services on auditor
             independence but ignore the role of market forces (Craswell et al.
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             1995; Larcker and Richardson 2004; Ruddock et al. 2006).
             Therefore, to explore the effect of market forces on the
             relationship between non-audit services and accounting
             conservatism is potentially interesting.
                      Research purposes
               This paper aims to extend the literatures of non-
             audit services research, and further explore the
             impacts of market forces on the relationship
             between the provision of non-audit services and
             accounting conservatism from the viewpoint of
             corporate governance. I hope my research can
             provide additional evidence with respect to market
             forces definitely serve to discipline auditors from
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             compromising their independence.
              Research design-Hypotheses development
              H1: Ceteris paribus, the auditors’ fee dependence
               is negatively associated with the level of
               accounting conservatism. .


              H2: Ceteris paribus, the negative effect of
               auditors’    fee    dependence      on earnings
               conservatism is higher for firms with weak
               quality of board oversight than for firms with
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               strong quality of board oversight .
              Empirical methodology and variable measurement
                             Proxies for Auditor Independence:
              the ratio of non-audit fees to total fees
              abnormal non-audit fees based on the expectation models




              abnormal total fees based on the expectation models
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              Empirical methodology and variable measurement
                      Proxies for Board Characteristics:
              This paper employs four characteristics for board of director to
               shed light on the independence and monitoring motivation of
               the board: (i) Percentage of independent directors and
               supervisors on the board, (ii) Percentage of family directors
               and supervisors on the board, (iii) CEO duality, and (iv) Board
               size.
              The percentile rank method is applied to the four individual
               measures of board characteristics-INDEP, FAM, CEO, and
               BOSIZE-to drive an overall governance score which I denote
               as CGTS (Milliron 2000; Bushman et al. 2004). For the
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               following analysis, this paper will use the aggregate CGTS
               measure as a proxy for board characteristics governance.
              Empirical methodology and variable measurement
                    Measurement of Accounting Conservatism:
              The accrual-based conservatism measure (hereafter
               ACCRUAL) is computed as follows: Net income before
               extraordinary items plus depreciation expense less cash flows
               from operations is deflated by average total assets, and
               averaged over 3 years centered around year “t”.
              Basu’s asymmetric timeliness of earnings measure with the
               backward-cumulation approach.
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              Empirical methodology and variable measurement
              Empirical model for tests using accrual-based conservatism
               measures is as follows:




                  According to H1, as auditors reduces their independence, the
               level of accounting conservatism will decrease, therefore, I
               predict that β1 >0. Furthermore, β3 represents the incremental
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               effect of client importance on accounting conservatism for
               firms with strong board governance. If H2 is valid, then I
               would predict that β3 <0.
                  Empirical methodology and variable measurement
             ACCRUAL: net income before extraordinary items plus depreciation expense less cash
                       flows from operations deflated by average total assets and averaged over
                       3 years centered around year t;
               CLIMP: three measures of client importance that focus on the ratio of non-audit
                       fees to total fees, abnormal total fees and abnormal non-audit fees;
               BOARD: an overall governance scores for board characteristics driven by the
                       percentile rank method;
                 SIZE: the natural logarithm of average total assets;
                  LEV: total long-term liabilities divided by average total assets;
                SAGR: percentage of annual growth in total sales;
                 INST: ratio of sum of foreign institutional, securities investment trust
                       enterprises’ and securities firms’ ownership to total ordinary shares
                       outstanding;
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                RDAV: research and development costs plus advertising expense divided by sales;
                 CFO: cash flows from operations deflated by average total assets;
                  IMR: the inverse Mill’s ratio obtained from the two-stage Heckman (1978)
                       approach;
                    ε: residual;
              Empirical methodology and variable measurement
             Empirical model for tests using Basu’s asymmetric timeliness of earnings
             measure is as follows:
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             Under Basu (1997) regression specification, I expect the coefficient for
             β13 to be significantly negative. According to H2, I predict that the
             coefficient of β21 will be significantly positive.
                  Empirical methodology and variable measurement
                 Et, t-j: income before extraordinary items cumulative from year t-j to year t;
                 Pt-j-1: the market value of equity at the end of the year t-j-1;
                 Rt, t-j: the buy-and-hold return starting 4 months after the end of the fiscal year t-j-1
                          and ending 4 months after the end of year t;
               DRt, ,t-j: a dummy variable is equal to one if DR is negative, zero otherwise;
                MTBt: market-to-book ratio defined as market value of equity divided by book value
                     of equity at the end of current year;
               LEVt: total long-term liabilities divided by average total assets;
             CLIMPt: three measures of client importance that focus on the ratio of non-audit fees to
                     total fees, abnormal total fees and abnormal non-audit fees;
             BOARDt: an overall governance scores for board characteristics driven by the percentile
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                     rank method;
               IMRt: the inverse Mill’s ratio obtained from the two-stage Heckman (1978) approach;
                  ε: residual;
                        Sample formation and data resources
              TABLE 2 Sample Selection and Sample Breakdown by Industry from 2002 to 2006
             Panel A Sample Selection                                                    Total
             Number of firm years with complete data for estimated proxy measure for
                                                                                          412
             abnormal fees (after the exclusion of Financial Institution)
             Missing the inverse Mill’s ratio data                                        10
             Missing board characteristics data in the annual report                      74
             Missing one or more variables related to earnings conservatism measure
                                                                                          58
             model
             Final sample                                                                 270

             Panel B Sample Breakdown by Industry
                                              Industry                                 Firm-years
             Chemicals                                                                     6
             Cement                                                                        5
             Automobile                                                                    8
             Glass ceramics                                                                3
             Food                                                                          7
             Textiles                                                                      8
             Shipping and transportation                                                   2
             Information service                                                           1
             Paper pulp                                                                    1
             Trading and consumers' goods                                                  2
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             Plastics                                                                      11
             Electron                                                                     149
             Electronic and cable                                                          2
             Electronic machinery                                                          20
             Rubber                                                                        7
             Iron and steel                                                                12
             Building material and construction                                            9
             Other                                                                         17
               Sample formation and data resources
                               sample period
        the sample period spans five years from 2002 through 2006.
                                data sources
        Regarding data sources, except for the board characteristics
         variables which are manually collected from the annual reports,
         the regression variables required for estimating accounting
         conservatism and other financial variables of the empirical
         model are all collected from the TEJ database and the Times
         Winner database.
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        The demand for non-audit services may depend upon firm’s
         economic characteristics. To address this self-selection bias
         issue, my study uses the two-stage procedure of Heckman
         (1979) to solve the problem.
                V
                     Empirical results and analysis-Table 5
                 ariable     Predicted sign     Model 1     Model 2      Model 3
                                                 0.222        0.202        0.226
             Intercept
                                              (0.000)***   (0.000)***   (0.000)***
                                   +             0.034
             NAFTF
                                               (0.033)**
                                   +                         -0.012
             RESITF
                                                            (0.167)
                                   +                                        0.005
             RESINAF
                                                                         (0.025)**
                                                 0.035         0.015        0.011
             BOARD                 ?
                                              (0.005)***    (0.049)**     (0.187)
             CLIMP*                             -0.093        -0.057       -0.011
             BOARD                 -          (0.007)***   (0.000)***    (0.012)**
                                                -0.010        -0.009       -0.010
             SIZE
                                   ?          (0.000)***   (0.001)***   (0.001)***
                                                -0.059        -0.058       -0.059
             LEV                   -
                                              (0.005)***    (0.014)**    (0.023)**
                                                 0.034         0.028        0.033
             SAGR                  +
                                              (0.008)***    (0.016)**   (0.008)***
                                                 0.107         0.110        0.106
             INST                  ?
                                              (0.001)***   (0.003)***    (0.010)**
                                                -0.159        -0.144       -0.156
             RDAV                  -
                                              (0.003)***   (0.003)***   (0.005)***
                                                -0.334        -0.321       -0.331
             CFO                   -
                                              (0.000)***   (0.000)***   (0.000)***
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                                                -0.031        -0.023       -0.031
             IMR                   ?
                                              (0.001)***   (0.006)***   (0.001)***

                                                 -0.059      -0.069       -0.007
             β2+β4                 -
                                               (0.043)**   (0.000)***    (0.094)*
              Adjusted-R2                       31.16%       37.39%       30.67%
               F Statistic                      13.178       17.063       12.901
               (p-value)                      (0.000)***   (0.000)***   (0.000)***
                   N                              270          270          270
             Empirical results and analysis-Table 6
                      Variable   Predicted sign     Model 1      Model 2      Model 3
                                                       0.399       0.513         0.406
              Intercept                ?
                                                     (0.101)    (0.019)**     (0.071)*
                                                      -2.246       -2.228       -1.891
              DR                       -
                                                  (0.001)***   (0.002)***   (0.001)***
                                                       0.337       0.239         0.319
              R                        +
                                                   (0.031)**     (0.074)*    (0.025)**
                                                      -4.168       -4.285       -3.981
              R*DR                     +
                                                  (0.009)***   (0.003)***   (0.005)***
                                                       0.035       -0.009        0.020
              MTB                      ?
                                                     (0.384)      (0.805)      (0.598)
                                                       0.171       0.432         0.086
              MTB*DR                   ?
                                                     (0.230)    (0.019)**      (0.555)
                                                      -0.013       -0.006       -0.013
              MTB*R                    ?
                                                   (0.032)**      (0.279)    (0.035)**
                                                      -0.103       0.074        -0.187
              MTB*R*DR                 -
                                                     (0.411)      (0.444)      (0.353)
                                                      -0.374       -0.259       -0.263
              LEV                      ?
                                                     (0.185)      (0.277)      (0.326)
                                                       2.379       2.531         2.679
              LEV*DR                   ?
                                                  (0.005)***   (0.008)***   (0.004)***
                                                       0.088       0.063         0.054
              LEV*R                    ?
                                                     (0.506)      (0.609)      (0.703)
                                                       5.340       6.561         6.066
              LEV*R*DR                 +
                                                  (0.001)***   (0.001)***   (0.001)***
                                                       0.232       0.574         0.046
              CLIMP                    ?
                                                     (0.543)   (0.005)***      (0.419)
                                                       1.534       -1.054        0.415
              CLIMP*DR                 ?
                                                    (0.057)*   (0.001)***     (0.097)*
                                                      -0.131       -0.385       -0.009
              CLIMP*R                  ?
                                                     (0.718)   (0.006)***      (0.805)
                                                       2.225       -1.649        0.825
              CLIMP*R*DR               -
                                                     (0.241)    (0.016)**      (0.197)
                                                       0.089       0.092         0.068
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              BOARD                    ?
                                                     (0.498)      (0.186)      (0.308)
                                                      -0.156       0.135         0.569
              BOARD*DR                 ?
                                                     (0.752)      (0.552)    (0.023)**
                                                       0.113       0.054         0.041
              BOARD*R                  ?
                                                     (0.223)      (0.206)      (0.324)
                                                      -1.717       0.331         1.145
              BOARD*R*DR               ?
                                                     (0.106)      (0.530)    (0.032)**
                                                      -0.003       -0.682       -0.047
              CLIMP*BOARD              ?
                                                     (0.995)   (0.003)***      (0.498)
                                                       1.838       1.880         0.291
              CLIMP*BOARD*DR           ?
                                                     (0.161)   (0.000)***      (0.373)
                                                      -0.402       0.423         0.005
              CLIMP*BOARD*R            ?
                                                     (0.328)   (0.007)***      (0.901)
                     Empirical results and analysis-Table 6
                                       Table 6 (continued)
                                    Predicted
                       Variable                    Model 1     Model 2      Model 3
                                      sign
                                                      8.194       3.886        1.347
             CLIMP*BOARD*R*DR           +
                                                 (0.000)***   (0.000)***    (0.056)*
                                                     -0.085      -0.134       -0.078
             IMR                        ?
                                                    (0.471)     (0.274)      (0.528)
                                                      0.366       0.449        0.324
             IMR*DR                     ?
                                                  (0.020)**    (0.046)**     (0.115)
                                                     -0.167      -0.109       -0.152
             IMR*R                      ?
                                                   (0.060)*     (0.119)     (0.094)*
                                                      1.085       1.134        1.031
             IMR*R*DR                   ?
                                                 (0.000)***   (0.000)***   (0.000)***

                                                  10.419         2.237        2.171
             β13+β21                   +
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                                                (0.000)***     (0.016)**   (0.000)***
                     Adjusted-R2                  51.08%        50.65%       49.47%
                      F Statistic                 10.437        10.274        9.848
                      (p-value)                 (0.000)***    (0.000)***   (0.000)***
                          N                         245           245          245
                                 Robustness tests
              I rerun the analyses after deleting the outliers and the results
               do not change.
              I repeat all tests reported in Tables 5 and 6 with board
               governance based on outside directors and supervisors in
               replace of independent counterparts, all results are not
               qualitatively affected.
              I perform book-to-market ratio tests following Beaver and
               Ryan (2000) as another conservatism measure.
              The paper further investigates the impacts of alternative
               market forces such as litigation risk and reputation loss on the
               relationship between client importance and accounting
               conservatism.
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              To ensure that the clients of any one audit firm are not driving
               the results, I form five separate subsamples by deleting in turn
               the clients of each of the Big 4 firms and non-Big 4 firms at a
               time.
                  Summary and concluding remarks
              Empirical results reveal that the impairment of
               auditor independence is significantly associated with
               the reduction of conservatism. Especially, I further
               find that sound board governance mechanisms
               definitely offset the effect of aggressive accounting
               caused by impaired auditor independence.
              Collectively, these findings are consistent with the
               view that board governance is the primary
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               determinant of auditor’s attitude toward conservative
               accounting.
             Thank you for your attention!
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