# A Counterfactual Impact Analysis of Fair Use Policy on Copyright Related Industries in Singapore: A Critical Review

## Abstract

**:**

## 1. Introduction

## 2. Background on the Difference-in-Differences Estimator

^{T}is the outcome of the treated group and Y

^{C}the control group (Meyer 1995, p. 155). The subscripts 0 and 1 indicate, respectively, the outcomes before and after the treatment. Equation (1) shows clearly why the method is referred to as a difference-in-differences estimator; it is literally the difference between two differences.

## 3. Summarizing the Fair Use Study

We posit that flexible fair use in copyright law has two additional effects in the economy beyond those posited by traditional fair use analyses. Flexible fair use exemptions may: (1) increase the growth rate of private copying technology industries; and (2) increase the growth rate of copyright markets. We test this hypothesis using a differences-in-differences methodology that is applied to the 2005 fair use amendments to the Singapore Copyright Act and test its implications on private copying technology and copyright sectors in Singapore.

_{t}= β

_{0}+ β

_{1}t + e

_{t}

_{t}is the value-added figure and t is a time indicator (t = 1, 2, …, 6). Using the estimated β

_{0}and β

_{1}coefficients from Equation (2), the authors compute the value of y in the final period (y

_{12}, six years later in the year 2010, ignoring the data from 2005 through 2009), and this prediction serves as the pre-treatment value (or untreated value) of y (or ${Y}_{0}^{T}$ from Equation (1)). For example, data from the Private Copying group produces the “prediction” equation:

_{t}= 0.06338 − 0.00388t

## 4. The Empirical Analysis

#### 4.1. Multiple Treatments

#### 4.2. Hypothesis Testing and Sample Sizes

#### 4.3. Dimension Problems

#### 4.4. The Parallel Paths Assumption

#### 4.5. Additional Issues

_{t}− y

_{t}

_{−1}). Without data from 1998, this produces a missing value for year 1999, which reduces the sample size from 12 years to 11 years. Looking at Table A5, however, rather than excluding 1999 from the data as a missing value, the authors have inserted “0” as a data point for that year. The regression results from Table A4 indicate there are 12 observations in the regression, which implies that the “0” observation for 1999 was, in fact, included in the estimation (I was able to replicate the results to confirm this error).

## 5. A Standard Estimation Technique

_{it}= δD

_{it}+ βX

_{it}+ λ

_{t}+ μ

_{i}+ ε

_{it},

_{it}is the outcome for observation i at time t, D

_{it}is a dummy variable that equals 1 if the observation is treated in year t (0 otherwise), X

_{it}is a vector of control variables that vary by observation and time, μ

_{i}is a fixed effect for each observation i, λ

_{t}is a time effect common to all observations in time t, and ε

_{it}is the econometric disturbance term that is assumed to be distributed independently of all μ and λ (Angrist and Krueger 1999, p. 1294). The δ and β

_{1}are also estimated parameters. This model is a two-way fixed effects model (that is, there are dummy variables for each series and each time period). These dummy variables address the dimension problem and account for broader economic shocks (Angrist and Krueger 1999, pp. 1293–99).

_{it}falls out of Equation (4). The data is measured as “value added” of various sectors in the economy, which I label v

_{it}. Thus, Equation (4) can be simplified to:

_{it}= δD

_{it}+ λ

_{t}+ μ

_{i}+ ε

_{it},

_{it}is a dummy variable equal to 1 for the Private Copying or Copyright groups beginning in year 2005 (0 otherwise). The regression is a two-way (SSIC, time) fixed effects regression with a dummy variable that equals 1 for the treatment groups during the treatment period (2005 to 2010). Standard errors are clustered on the SSICs, as is recommended in the literature (Bertrand et al. 2004).

^{2}of the regression is 0.05 and the F-statistic is 4.34 (prob < 0.01). The estimated treatment effect (δ) for the Private Copying group is 0.00074 with a t-statistic of 0.30 (prob = 0.77); the effect is not statistically different from zero. The null hypothesis of “no change” in the Private Copying group’s outcomes before and after 2005 cannot be rejected. For the Copyright group, the estimated treatment effect (δ) is equal to 0.00034 with a t-statistic of 0.81; the effect is not statistically different from zero (prob = 0.43). The null hypothesis of “no change” in the Copyright group’s outcomes before and after 2005 cannot be rejected. Thus, the modifications to Singapore’s copyright law are found to have had no effect on the economic outcomes that Ghafele and Gibert deemed of interest.4

## 6. What if the Results Were Right?

## 7. Conclusions

## Funding

## Conflicts of Interest

## References

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1 | An alternative interpretation of the results is that the analysis shows a huge forecast error for the Private Copying group and small errors for the Copyright and Control groups. |

2 | A possible case where both the treated and control groups receive the treatment but the control group remains valid (possibly) is if the control group is genetically immune from the disease being treated (or the treatment itself). Even so, the control group would be suspect. |

3 | Each series is mean-centered (on unity) for illustration purposes. |

4 | Given problems with the data, control group, and the parallel paths assumption, I do not contend that these findings are actually valid. Rather, if I take Ghafele and Gibert’s general approach and apply proper statistical test, no effect is found. |

Industry Group | 2010 Actual | 2010 Predicted | Diff. | Impact (Adj. for Control) |
---|---|---|---|---|

Private Copying | 5.02% | 1.68% | 3.34% | 3.33% |

Copyright | 0.55% | 0.78% | −0.23% | −0.25% |

Control | 0.44% | 0.43% | 0.01% | … |

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**MDPI and ACS Style**

Ford, G.S. A Counterfactual Impact Analysis of Fair Use Policy on Copyright Related Industries in Singapore: A Critical Review. *Laws* **2018**, *7*, 34.
https://doi.org/10.3390/laws7040034

**AMA Style**

Ford GS. A Counterfactual Impact Analysis of Fair Use Policy on Copyright Related Industries in Singapore: A Critical Review. *Laws*. 2018; 7(4):34.
https://doi.org/10.3390/laws7040034

**Chicago/Turabian Style**

Ford, George S. 2018. "A Counterfactual Impact Analysis of Fair Use Policy on Copyright Related Industries in Singapore: A Critical Review" *Laws* 7, no. 4: 34.
https://doi.org/10.3390/laws7040034