Category Archives: Role of the Media



D. Stromberg

The Quarterly Journal of Economics Vol. 119, No. 1 (2004) pp. 189-221

Principal Research Question and Key Result Does penetration of mass media such as radio create better informed voters that consequently receive more favourable policies? In the context of early radio expansion, this paper finds that an increase in the share of households with a radio by 1% increases spending in that area by 0.54%. 
Theory Mass media creates a distribution of informed an uninformed citizens. Informed citizens may be able to achieve better policy results. For this to occur they must vote, and they must know whether their representative has done something for them, and information from the media helps them. Thus is it more costly for politicians to neglect voters with access to political information via the media. This indicates that government spending s should be higher on groups that have access to the media, higher on groups where more people vote and voter turnout should be higher where people have access to media.The model indicates that if:

xi(uc)(zc) – βi η > ui

then the incumbent will be reelected. X is 1 if the population knows that something has been done for them. U is the utility they receive from the amount of spending Z. Beta is the ideological preference for the challenger, and Eta is the general popularity of the other candidate.

The governor knows that the voter will vote with some probability t and that the voter knows of his responsibility for the relief programme with some probability α that is an increasing function of r (radio coverage)

This generates the following propositions:

  1. If the voters cannot know if money is spent in their county or not (x = 0) then the politician has no incentive to spend there, as he will get no political credit for doing so.
  2. If Beta is distributed such that the ideological preference for the challenger is such that the incumbent cannot win, then he will not spend in that county as he will not be reelected in any case.
  3. He will allocate more funds where there are more gains to be had on the margin i.e. where turnout is higher, and there are more radios, there are more swing voters and the need for relief spending is high (where Uc is high).


Data 2500 US counties in panel from 1920-1940. This was in the middle of radio expansion, and also during the FERA programme which distributed funds to those whose income was inadequate to meet their needs. It was locally administered and local officials decided who would and would not receive the assistance. Governors were the main arbiters.

Ln(zc) = αln(rc) + βln(tc) + δ1xc1 +εic

State specific fixed effects are also included and standard errors are clustered within state. The main hypothesis is that α>0


Results Factors indicating low socio-economic status are positively correlated with spending indicating that income assistance was directed to places where utility was likely to be highest (i.e. where they needed it most).The elasticity of spending with regard to radio ownership imply that increasing radio coverage by 1% would raise spending by 0.54%, and increasing turnout by 1% increases spending by 0.57%. The most important explanatory variable is unemployment which indicates that this was not just pork barrel politics, but that spending was directed where it was needed.

If radio use increases turnout, and turnout increases spending, then this is another mechanism through which radio is working. A fixed effects PANEL regression is estimated with turnout as dependent variable, with a host of controls. The coefficient on radio coverage is 0.117 and significant at 5% levels. Thus increasing radio coverage by 10% would increase turnout by 1.2%. Since every increase of 1% of turnout increases spending by 0.57% then the effect of radio on spending through turnout is 0.12*0.57 = 0.07%.


Robustness It is recognized that there could be bias in the estimates. Specifically, if richer counties (not otherwise captured by controls) have lots of radios, but no need of assistance then results would be downward biased. But it more people seek out radio ownership and are also better at getting their preferred policies, then this would create upward bias. In recognition of this, he implements an IV strategy, which uses geological features ground conductivity and woodland cover as instruments for radio ownership (as these variables both affect the quality of the received signal). The F-stats in the first stage are all strong. Exogeneity might be questioned, as geological features especially wood cover could be correlated with poverty or exclusion and hence relief spending which would downward bias the IV estimates. However, despite these concerns the IV results are actually more positive than the OLS results. As the author therefore takes the OLS results as his baseline, the IV just indicates the direction of the bias (i.e. people seek out radios who are better at getting what they want), and as such the main results of the paper are conservative, and this lends credence to the story.Property values, employment stats, income, wages, bank deposits etc. are all controlled for as well as share of votes in last election, voter density etc.

If the model is correct there should be more spending where elections were more closely fought. This is tested by excluding noncompetitive states, and the coefficients are nearly twice as large.

The effects should be larger in rural areas, as urban dwellers had better access to other types of media. When the specification is tested on a rural subsample the coefficient increases nearly 50%

If radio use is simply proxying for some other variable relating to the use of consumer durables then we should see similar results for other durables e.g. car ownership. Indeed gasoline sales are shown to have correlations with wages, employment etc. (just as radio does), but gasoline sales per capita are not related to spending in regressions.


  • This is a cross section, with data being pooled cumulatively. Panel data would have been ideal as we could see how outcomes changed with increased radio penetration, and particularly if funds are limited, then as radio coverage becomes near universal the limited pot of FERA funds may not be significant enough for use for political capital in all counties covered by radio. This would be akin to a general equilibrium effect. Panel data would have allowed.
  • Sadly no interaction terms are used. For example an interaction term between unemployment and radio coverage could have given an estimate of the differential effect that radio coverage has in the presence of a given level of unemployment, or need. This would have been interesting to see, as the levels estimates are not as readily intelligible.


Implications Mass media can carry politically relevant information to voters who can then use this to update their voting positions. This can make politicians more accountable as people are more likely to vote.Simply extending the franchise to the poor is not enough as this paper makes clear. What is important is how informed people are, for if certain sections are not informed as to the spending policies of the government, then such spending may be cut without fear of losing votes, and redirected to areas that may have less objective need for the spending.

As the inclusion of welfare indicators made the estimates stronger it seems clear that spending was not just directed at those who were rich enough to own radios.

The bottom line is that radio improved the relative ability of rural America to attract government transfers.






T. Besley & R. Burgess

Quarterly Journal of Economics (2002)

Principal Research Question and Key Result Does access to mass media, in particular to newspapers, increase the responsiveness of governments to the needs of the people? In other words does mass media mitigate political agency problems by providing information to voters? In the context of India, the authors find that newspaper circulation does indeed increase the amount of government responsiveness. A 1% increase in newspaper circulation is associated with a 2.4% increase in food distribution and a 5.5% increase in calamity spending.


Theory The general idea is that media enables vulnerable population to assess the actions of incumbents in order to inform their voting decisions.


Voters are of two types 1) vulnerable – meaning vulnerable to some shock (weather etc.), and 2) non-vulnerable. Of 1) there are a) needy – those for whom in the given time period a shock actually materializes, and b) non-needy – being the vulnerable who are not actually affected by a shock.


Incumbents are of three types 1)selfish – will never help the vulnerable 2)altruistic – will always help 3) opportunistic – will help if it increases chances of reelection. In order to help the incumbent has to exert an amount of effort  which is a cost to him.

The needy always observe how much effort has been applied, but the rest of the vulnerable population learns from the media. Effort is more likely to be learned about when the effort is greater, and the marginal impact of effort will be greater when there is more media.


Those who are needy in the first time period, and those who are vulnerable realize they may be affected by a shock in the next time period. Thus when they elect the official in the election that occurs between periods they want to maximize the chances of getting of getting a politician that will help them. (Formally, as there are only two periods in this set up, the opportunistic politician will not help in time 2, as he has no more reelection concerns, thus the voters want an altruistic politician. However they cannot observe the type directly). Thus they will always vote for the incumbent that helped them in time 1 as he is definitely not selfish and may turn out to be altruistic. By backward induction, this means that effort by an opportunistic incumbent is higher when:


  1. Voters have more media access
  2. There is higher turnout
  3. There is a larger vulnerable population
  4. The incumbent has a low advantage


Non-vulnerable citizens are thought to vote along ideological lines.


This can all be summarized thus: greater media activity raises the marginal value of effort because it is more likely that reports of the effort will find its way to voters. More turnout increases the effectiveness of effort by turning it into support at the ballot box, and the same is true when the vulnerable population is larger. Effort is greater when there is more competition

Motivation In the absence of well-functioning markets, the vulnerable sections of society are often reliant upon government action for protection. Of concern then is what institutions can be developed to ensure that the government does so protect its people. This question is particularly important given that poor people are less likely to be informed about politics, and also less likely to vote, so without good institutional design they could be totally excluded from benefitting from government, and also changing government.


Data Data are from Indian states that were responsible for administering public distribution of food and calamity relief. When the local governments were given this power there was also a huge increase in the number of newspapers that were being published, including a rise in local language publications. The press was relatively free and independent.

A panel from 1958-1992 is constructed that details public food distribution and calamity relief expenditure by state. The need for intervention is proxied by food grain productions and flood damage to crops variables. Newspaper circulation proxies for media penetration.


Strategy Fixed effects model.


git = αi + βt + γsit + δ(sit)(zit) + θ(zit) + εit


Where g is the outcome in state i  in time t. Alpha is state fixed, beta is time fixed effect. S captures the need for state intervention, and the effect of the need for intervention is captured by γ. This is effectively the “activist” component of government action i.e. how much the government is likely to respond to crisis. Z is a host of political variables that may affect government responsiveness including the media penetration variables.  Θ captures the effect these variables have on relief spending. The real coefficient of interest however is  δ as this captures the true “responsiveness” of government, in other words the differential response of governments to crisis in the presence of media (etc.). This will pick up whether responses are greater given more media, turnout, competition etc.


  • The effects of newspaper circulation are large and significant. A 1% increase in newspaper circulation is associated with a 2.4% increase in food distribution and a 5.5% increase in calamity spending.
  • Turnout in the last election, a measure of political competition, and dummies that indicate when elections are near at hand are included. Turnout does not seem to affect responsiveness. Competition is only significantly associated with food distribution not calamity relief, the same goes for being in an election year.
  • The coefficient on the interaction terms food production * newspaper circ is negative, indicating that for a given level of newspaper penetration, a fall in food production elicits are greater response in terms of food distribution. Similarly the interaction on flood damage * media penetration is positive, indicating that for a given level of newspaper circulation, more flood damage increases the amount of calamity relief offered.


  • They include a number of economic variables such as population density, income per capita etc. (as wealth etc. may increase media presence and relief spending), but none of the variables enter significantly. Thus it appears that economic factors have limited influence on government responsiveness.
  • The predict values of food grain production, by regressing the food grain production variable on state/year effects and the drought/flood variable, and used the predicted value (which essentially is the amount of grain that was affected by the weather shock) in the main specification. The results show that there is no relationship between the shock value of grain production and the outcomes, but there is a relationship between the shock value * media penetration interaction, which supports the interaction interpretation offered above.
  • The split out the papers by language and find that local language papers are much more important than English papers etc. (as they are more likely to report local news presumably – and vulnerable population is more likely to read in their local language).
  • There could be some OV problem that is not accounted for, so they instrument for media penetration using ownership on the basis that private ownership is more likely to be associated with bigger distribution as state owned media is more biased and thus there is less demand for their product.
  • They interact the other political variables with the proxies for need. And find that greater turnout is associated with greater responsiveness, as is political competition, although the effects for food distribution continue to be larger than for calamity relief.


  • The results may confirm the main hypothesis of the model (that increased media increases government responsiveness. However, other than this, results are quite mixed. In particular the other hypotheses of the model are not borne out for both food distribution and calamity relief. The authors claim that this is because food distribution is a more visible form of relief (and therefore easier to cash in on politically), but we might wonder whether this is sufficient.
  • It is not clear that newspapers should be the most important form of information dissemination. For example, if literacy is an issue in Indian states, then newspaper circulation may be informing a very specific subset of the population, and this may not be the vulnerable population. As the non-vulnerable population are said to vote on ideological grounds, then they cannot affect government responsiveness to crisis, and thus newspapers cannot be the driving force behind the observed responsiveness. Some measure of TV/radio penetration could have been included to see if/how the different forms of media substitute for each other. If TV/Radio are more likely to be in areas with high newspaper circulation (due to a high demand for information), then the newspaper variable could be picking up the effects of these other forms of media. The amount of these other media will be varying over time and by state so the fixed effects model cannot completely control for them.
  • The IV strategy is not great. The instruments are pretty weak (F = c. 5.5) and exogeneity is not well argued for i.e. greater private ownership of media sector could be associated with all sorts of political variables that might also affect relief spending. However, the estimates returned are much larger than the OLS estimates, which is a comfort, as the OLS estimates can then be thought of as lower bounds (perhaps due to attenuation bias from measurement error).


Implications Whilst democracy may be important for development, it is clear from this paper that simply amending the rules of the game will do little to change outcomes without a concurrent change in complimentary institutions. This paper shows that mass media and open political institutions can affect government activism and responsiveness. This confirms what Amartya Sen stated when he said that there have been no famines in India since the advent of democracy partly because newspapers make the fact known thus forcing issues to be faced by governments. The results indicate that civil society is thus a key component to a functioning democracy.