R_D_ Information Technology_ and Firm Performance by wanghonghx

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									Information Technology Risk and Return Trade-
     Off: New Evidence from Recent Data

               Gokcen Arkali, PVAMU
                       with
              Indranil Bardhan, UT-Dallas
              Vish Krishnan, UC-San Diego


                     YAEM 2010



                    July 1, 2010
Research Problem


To investigate the impact of IT investments on
               overall firm risk.




                                                 1
Positive Impact of IT on Firm Output
Levels
    Prior literature is rich in terms of productivity and profitability
     impact of IT but is limited in terms of explaining the IT risk-
                             return relationship.

   A significant amount of research has claimed that productivity
    paradox has been disappeared by showing positive impact of IT
    on firm output levels. (Brynjolfsson and Hitt 1996, Dewan and
    Min 1997)
   Dedrick et al. 2003 reviewed more than 50 published articles
    and concluded that higher levels of IT investments are
    associated with higher levels of productivity growth.
         Do higher IT investments impact the overall firm risk? How?

                                                                          2
Observed Impact of IT
   Kobelsky et al. (2008) empirically examine the impact of IT
    investments on earnings volatility and suggest two different
    explanations of the observed impact of IT:

       Implementation risk view: IT result in higher earning
        volatility compared to other capital investments.

       Information processing view: IT reduces the volatility of
        earnings.




                                                                    3
Prior Literature on the Impact of IT on
Firm Risk
   Kobelsky et al. (2008): IT increases the volatility of earnings
    however the increase is conditional upon firm-level contextual
    variables such as sales growth, unrelated diversification, and
    size.
   Dewan, Shi, and Gurbaxani (2007): Established a link between
    IT risk and return using a production function frame.
      IT is the most risky form of investment among all other non-

        IT capital investments.
      Firms that have higher IT risk also have higher IT returns

        compared to the firms that have lower IT risk.



                                                                 4
IT Risk and Return Trade-off
   We empirically explore the relationship between IT risk and
    firm returns.
   Dewan, Shi, and Gurbaxani (2007) empirically test the
    relationship between IT risk and firm returns and measure the
    magnitude of IT risk relative to other investments.
   We conduct a replication analysis to contribute to the stream of
    research initiated by Dewan et al. (2007) by a recent and
    unique data set to see the impact of newer technologies on
    overall firm risk.




                                                                    5
Modeling IT Risk
     i ,t   0  1 IT _ Assetsi ,t   2 K _ Assetsi ,t   3 Sizei ,t   4 Leveragei ,t
            5 R & Di ,t   6 Advi ,t   7 IndQi   8 InConci   9,k Yeark   i ,t




 We use pooled regression to estimate the average contribution of IT risk to the overall firm risk.

                                                                                                      6
Modeling IT Risk-Industry Segment
Level
We investigate IT risk at the industry segment level where the industry
segments are defined using two-digit NAICS codes.

                 J
   i ,t   0    1, j IT _ Assetsi ,t  IndCodei , j   2 K _ Assetsi ,t   3 Sizei ,t
                j 1

    4 Leveragei ,t   5 R & Di ,t   6 Advi ,t   7 IndQi   8 InConci   9,k Yeark   i ,t


IndCodei,j : 1 if firm i resides in industry segment j otherwise the value is 0.

α1,j : represents the average contribution of IT investment of industry sector j
on the overall firm risk.




                                                                                                      7
Modeling IT Return
We model the impact of IT capital, non-IT capital, and other control variables
on a standard Cobb-Douglas production function following Dewan et al. (2007)
in a log-linear form as shown below.

      ln VAi ,t   0  1 ln IT _ Assetsi ,t   2 ln K _ Assetsi ,t   3 ln LaborCosti ,t
                 4 IndQi ,t   5 IndConci ,t   6,k Yeark   i ,t

VAi,t denotes the valued-added for firm i in year t. Value-added is essentially
the sales (data12) minus the cost of goods sold (data41).
LaborCost is obtained from Compustat data item data42. As consistent with
Dewan et al. (2007), the marginal product of IT capital is defined as follows.




                                                                                               8
Data Collection
   IT Data:
        Obtain firm-level IT spending data from an international research firm
         through the annual surveys whereas Dewan et al. (2007) obtains firm-
         level IT stock data from the Computer Intelligence Infocorp (CII)
         installation database.
        Our baseline dataset spans a recent time period from 1997 to 2004
         permitting us to see the impact of post-Internet era whereas Dewan et al.
         (2007) dataset covers years 1987 to 1994.
   Financial and Accounting data are obtained from Standard and Poor’s
    Compustat database.
   Daily raw return data are obtained from Center for Research in
    Security Prices (CRSP) stock price database.
   Missing data for advertising from year 2002 to 2006 has been
    supported via the TNS Media Intelligence (TNSMI) database.



                                                                                9
   Descriptive Statistics
                           Variable               Mean                   Std. dev.              Minimum                Maximum

                           SdStock                0.033                  0.050                  0.007                  1

                           SdEarnings             0.593                  0.336                  0.006                  1

                           SdEquity               0.150                  0.260                  0.001                  1

                           ITCapital              381.82                 873.62                 0                      14599.95

                           KCapital               12894.01               35292.75               0.001                  529040.54

                           IT_Assets              0.031                  0.032                  0                      0.396

                           K_Assets               0.559                  0.213                  0.009                  0.960

                           Size                   8.44                   1.79                   0.155                  13.03

                           Leverage               0.274                  0.209                  0                      2.14

                           R&D                    0.055                  0.141                  0                      3.35

                           Adv                    0.021                  0.055                  0                      1.80

Notes. 1. All variables including IT capital, non-IT capital, Assets, Sales, Market value of equity, Debt, and Advertising are measured in millions of dollars.
2. The dependent variables are winsorized by setting the values that are greater than one to be equal to one; we provide the winsorized statistics in the above
table.
                                                                                                                                                                  10
                                                 Table 4.2. Descriptive Statistics of Model Variables
Industry Partitioning to Estimate IT
Risk
  2-digit    Industry Segment            Ind. Code       N (firms)
  NAICS
  22         Utilities                   Ind1            41
  31,32,33   Manufacturing               Ind2            245
  42         Wholesale Trade             Ind3            42
  44,45      Retail Trade                Ind4            27
  48,49      Transportation and          Ind5            18
             Warehousing
  51         Information                 Ind6            40
  52         Finance and Insurance       Ind7            78
  54         Professional, Scientific,   Ind8            24
              and Technical Services
  56         Administrative and          Ind9            11
             Support
             and Waste
             Management and
             Remediation Services
  62         Health Care and Social      Ind10           9
             Assistance
  72         Accommodation and           Ind11           13
             Food Services


                      Table 4.3. Industry Partitioning               11
Empirical Analyses
   We present the empirical results for the two underlying
    empirical models:
       Estimating the contribution of IT investments on overall firm risk
       Estimating the relationship between IT risk and return using the
        production function framework.


   Then, we perform various robustness checks for the
    production function analyses.




                                                                             12
Empirical Results: Estimating IT Risk
                         Replication                       Original Study (DSG, 2007)
        Panel A: Dependent variable is earnings volatility (SdEarnings)
        Variable   2-digit NAICS Industry-structure 2-digit SIC Industry-structure
        IT_Assets -0.052***          -0.079***             0.619***       0.567***
        K_Assets 0.046***            0.020                 0.016***       0.008**
        Size       -0.326***         -0.292***             -0.0008**      -0.004***
        Leverage 0.095***            0.059***              0.028***       0.009**
        R&D        0.035**           0.040**               0.182***       0.182***
        Adv        -0.086***         -0.081***             0.048**        0.012
        IndQ                         -0.009                               0.0003
        IndConc                      -0.088***                            -0.006
        Adj. R2    0.15              0.10                  0.539          0.546
        Panel B: Dependent variable is stock-returns volatility (SdStock)
        IT_Assets -0.032*            -0.025                0.259***       0.125***
        K_Assets -0.009              0.012                 0.006***       -0.002**
        Size       -0.349***         -0.364***             -0.0005*** -0.003***
        Leverage 0.013               0.011                 0.018***       0.007***
        R&D        0.124***          0.122***              0.022***       0.030***
        Adv        -0.009            -0.016                0.017***       0.005
        IndQ                         0.003                                -0.0003
        IndConc                      0.061***                             0.0008***
        Adj. R2    0.1748            0.15                  0.859          0.885




                                                                                        13
Empirical Results: Estimating IT Risk

                                             Replication

    Panel C: Dependent variable is return on equity volatility (SdEquity)

    IT_Assets                     0.054***                       0.081***

    K_Assets                      -0.033**                       -0.036***

    Size                          -0.468***                      -0.447***

    Leverage                      0.123***                       0.099***

    R&D                           0.115***                       0.139***

    Adv                           -0.063***                      -0.042***

    IndQ                                                         0.083***

    IndConc                                                      0.022

    Adj. R2                       0.25                           0.21

    F Value                       51.06                          81.45
                                                                             14
Empirical Results: Estimating IT Risk




         Table 4.6. Low versus High IT Risk Industry Segments   15
Empirical Results: Estimating the
Return on IT
                       Replication                   Original Study (DSG, 2007)
                     Panel A: IT risk based on earnings volatility
                       Low IT-risk High IT-risk Low IT-risk High IT-risk
      Variable
                       subsample      subsample      subsample        subsample
      Ln (ITCapital) 0.286***         0.604***       0.017            0.098***
      Ln (KCapital)    0.460***       0.271***       0.238***         0.257***
      Ln (LaborCost) 0.258***         0.049          0.685***         0.607***
      IndQ             0.057          -0.151***
      IndConc          0.017*         0.185***
      IT marg. prod. 1.880            1.832          1.21             4.08
            2
      Adj. R           0.71           0.76           0.944            0.869
                   Panel B: IT risk based on stock-returns volatility
      Ln (ITCapital) 0.441***                        0.020*           0.094***
      Ln (KCapital)    0.283***                      0.277***         0.197***
      Ln (LaborCost) 0.235***                        0.632***         0.666***
      IndQ             0.038***
      IndConc          0.018**
      IT marg. prod. 2.915                           1.33             3.36
            2
      Adj. R           0.75                          0.926            0.860

                                                    VAavg
                    IT m arg inal product  1 
                                                     ITavg

                                                                                  16
Robustness Checks




        Table 4.8. Robustness Checks for Production Function Analyses   17
Key Findings
   Our results on the impact of IT on firm risk:
       Impact of IT on the overall firm risk is negative or not significant when
        the risk is measured by volatility of earnings or stock-returns as opposed
        to the findings of Dewan et al. (2007) for the same risk measures.
       Partial support for Dewan et al. (2007) on the positive and significant
        impact of IT on firm risk as measured by the volatility of ROE.
   The reducing impact of IT risk reveals the “information
    processing view of IT” as opposed to the “implementation risk
    view of IT” supported by Dewan et al. (2007).
       IT acts as a stabilizer on earnings by better coordinating the information.
   Our results support the high return on IT across the high IT risk
    industry segments similar to the findings of DSG (2007).


                                                                                 18
Questions?

								
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