# **VI. Discussion of the results**

## **Analysis section**

The primary theory that we are testing in this paper is whether mass media has the ability to influence political actions. We use the _Doing Business_ data as a proxy to test the set hypothesis. Specifically, we analyze whether media coverage of _Doing Business_ serves as an impetus for the implementation of business regulatory reforms. An innocuous argument could be that countries that are active reformers on _Doing Business_ indicators naturally tend to have higher media coverage. But can media coverage actually spur reforms and turn regulations into actionable outcomes? To answer the posed question, we collected primary data on media coverage for 190 countries worldwide. Using Factiva and Google databases we were able to compile a comprehensive panel data set, perfectly matching _Doing Business_ historical time series on the number of implemented reforms as well as the Doing Business scores and rankings ( _see_ section on methodology outlining the data collection process and limitations).

To explore strengths and directions of relevant correlations, we first run a number of simple OLS regressions with the latest data at hand ( _Doing Business_ 2018). In line with the set hypothesis, the primary dependent variable - “Reforms” - comprises absolute numbers of implemented _Doing Business_ reforms by each of the sampled 190 economies over a given period of time. The set parameters for our applied OLS regression model are the following:

## **<mark>Model 1:</mark>** <mark>Reforms</mark> j <mark>� α</mark> 0 <mark>� α</mark> 1 <mark>local_media</mark> j <mark>�</mark> _<mark>β</mark>_ <mark>X</mark> j <mark>� ε</mark> j

The explanatory variable “local_media” captures country-specific _Doing Business_ media coverage in terms of numbers of local media articles addressing _Doing Business_ in a given year (spanning over the time period between the publication of two consecutive _Doing Business_ reports). Our logical assumption is that media coverage’s impact on reform implementation is not immediate. A certain period of time needs to elapse between media coverage of _Doing Business_ and possible subsequent regulatory changes. Therefore, we construct the regression model with both one and two-year time lags between the dependent and independent variables, with media coverage variable lagging behind. Also, for this model we employ a standard set of controls represented as Xj. The controls include income per capita, degree of free press and levels of Doing Business scores.

Subsequently, we test a logit regression model (Model 2) with a binary outcome variable being whether a country reformed on _Doing Business_ indicator(s) over a set period of time or not. The explanatory variable in this model remains the number of local Factiva articles – “local_media” (with both one and two-year lags) and we use the same standard set of controls, represented by _Xj._ In addition, in Model 2 we control for the number of total media outlets in each country as coefficients could be inflated in economies with high media outlet concentration.

## **Model 2** : Pr�reformer� �1��F� γ� � γ�local_media� � βX� � ε��

In the following OLS regression model (Model 3) we use year on year deltas of _Doing Business_ scores (∆ DTF� as an outcome variable since countries’ performance can either improve or deteriorate over time. Improvements on the Doing Business measure and the magnitude of such improvements are commonly driven by the pace and impact of reforms. In Model 3, as in the previous two models, number of local media articles covering _Doing Business_ serves as an 17