Sustainable development in three newspapers: How does coverage in a particular newspaper influence other newspapers’ attention to sustainable development? - Vector autoregression
Upcoming SlideShare
Loading in...5
×
 

Sustainable development in three newspapers: How does coverage in a particular newspaper influence other newspapers’ attention to sustainable development? - Vector autoregression

on

  • 824 views

Sustainable development in three newspapers: How does coverage in a particular newspaper influence other newspapers’ attention to sustainable development?

Sustainable development in three newspapers: How does coverage in a particular newspaper influence other newspapers’ attention to sustainable development?
Vector autoregression

Statistics

Views

Total Views
824
Views on SlideShare
824
Embed Views
0

Actions

Likes
0
Downloads
4
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft Word

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Sustainable development in three newspapers: How does coverage in a particular newspaper influence other newspapers’ attention to sustainable development? - Vector autoregression Sustainable development in three newspapers: How does coverage in a particular newspaper influence other newspapers’ attention to sustainable development? - Vector autoregression Document Transcript

  • Sustainable development in three newspapers: How does coverage in a particular newspaper influenceother newspapers’ attention to sustainable development? Vector autoregression Assignment 4 Mark Boukes (markboukes@Hotmail.com) 5616298 1st semester 2010/2011 Dynamic Data Analysis Lecturer: Dr. R. Vliegenthart December 9, 2010 Communication Science (Research MSc) Faculty of Social and Behavioural Sciences University of Amsterdam
  • Table of contentsINTRODUCTION.............................................................................................................................................1METHOD........................................................................................................................................................1RESULTS........................................................................................................................................................2 VAR MODEL...........................................................................................................................................................2CONCLUSION.................................................................................................................................................8REFERENCE....................................................................................................................................................8DO FILE:.........................................................................................................................................................9
  • IntroductionIn this study I aim to investigate the influence news coverage in a particular newspaper has onthe coverage of another newspaper, and viceversa. For this purpose I have chosen a specifictopic, sustainable development, that seems to get a lot media attention in the last years. Thetopic of sustainable development was chosen, because it can be related to several parts ofsociety, such as the economy, science and also for the man in the street this topic is relevant. As those different parts of society are represented by different media, it is interesting tosee how they influence each other on the amount of attention that is paid to this issue. Will anincrease in attention of business men’s newspapers result in an increase of attention innewspapers that deal for a large part with science; and is this also occurring the other wayaround? How is the attention in a popular newspaper caused by or perhaps causing itselfattention in scientific or economic newspapers. The most read popular newspaper in theNetherlands is De Telegraaf, a newspaper that has a main economic or business focus is HetFinancieele Dagblad, and NRC Handelsblad is known for its relative large attention toscientific developments. To study the relationship between the attention to sustainable development in newscoverage of these three newspapers, my main research question was: Does the amount ofattention in one newspaper for sustainable development cause attention in the othernewspapers and viceversa? The sub research questions were therefore the following: • Did the amount of attention to sustainable development in De Telegraaf causes the amount of attention in NRC Handelsblad? • Did the amount of attention to sustainable development in NRC Handelsblad causes the amount of attention in De Telegraaf? • Did the amount of attention to sustainable development in Het Financieele Dagblad causes the amount of attention in NRC Handelsblad? • Did the amount of attention to sustainable development in NRC Handelsblad causes the amount of attention in Het Financieele Dagblad? • Did the amount of attention to sustainable development in Het Financieele Dagblad causes the amount of attention in De Telegraaf? • Did the amount of attention to sustainable development in NRC Handelsblad causes the amount of attention in De Telegraaf?MethodA dataset was created via a computer assisted content analysis that was conducted using thedigital archive of LexisNexis. Articles were selected via the Boolean search term duurza! OR"groene energie" OR "zonne-energie" OR "windenergie". The period I analyzed was from 1 1
  • January 1999 until 31 December 2009. This period was chosen, because information about DeTelegraaf is only available from 1999. The search procedure was repeated three times; one timefor every newspaper, so three variables could be created by aggregating the data on a weeklybasis. A total of 35225 articles were found for 581 weeks; 18501 in Het Financieele Dagblad,10335 in NRC Handelsblad and 6389 in De Telegraaf. To analyse the effects of the different newspapers on each other, a vector autoregression(VAR) analysis was conducted in Stata 10.1. A VAR analysis was chosen, because there are noclear theories about which variables are exogenous in which relations; in a VAR analysis all ournewspaper article variables could be endogenous. To control for possible effects of the variousclimate conventions that were held in the period under study, a dummy variable was created forthe weeks1 in which such conferences were held.ResultsI specify in this results section, how the VAR analysis was conducted and which results itfound. In doing this, I follow the procedure described by Brandt and Williams (2007).VAR modelFigure 1 plots the time series of the attention in the three newspapers for the period that we arestudying. It seems that Het Financieele Dagblad (FD) pays the most attention to sustainabledevelopment and De Telegraaf the least attention. The amount of attention seems to be quite stableover time, and that is also what augmented Dickey-Fuller tests confirm (see Table 1). Hypothesesfor unit root are rejected, so the data is treated as stationary and I did not need to integrate the data.Figure 1. The number of articles about sustainable development over time in the three newspapers of interest.1 Based on http://en.wikipedia.org/wiki/United_Nations_Framework_Convention_on_Climate_Change 2
  • Table 1. The results of augmented Dickey-Fuller tests for the amount of articles over time Augmented Dickey-Fuller test FD NRC TelegraafRandom walk without drift -4.990 -5.596 -6.560Random walk with drift -10.104 -14.525 -10.878Random walk with drift and trend -15.716 -16.751 -16.487Note. All tests indicate the absence of a unit root.In order to create the VAR, I had to select the appropriate number of lags for the model. Variousmodels were tested with lag lengths ranging from 1 to 8. Model fit statistics suggest that a modelthat includes either two (AIC= 20.93, SBIC= 21.11) or seven lags (AIC = 20.90, SBIC = 21.43)has the best fit. When lag-order selection statistics for the different VARs are studied, accordingto Akaike Info Criterion (AIC) and by inspecting the differences in Log Likelihood a VARmodel with seven lags is preferred; however, according to the Schwarzs Bayesian informationcriterion (SBIC) and the Hannan and Quinn information criterion (HQIC) the VAR model withtwo lags should be preferred. Finally, I chose to use the VAR model with 2 lags as this modelwas much more parsimonious and differences in AIC with models including more lags werevery small. To check whether this model can be used, the residuals of the three newspaper variablesin this model were tested for autocorrelation with the Ljung–Box Q test statistic and for thepresence of conditional heteroscedasticity with the Engle-Granger test. The residuals of thenumber of articles in Het Financieele Dagblad (Q = 26.33, p = .16) and NRC Handelsblad (Q =15.28, p =.76) reflected white noise, however the residuals of the number of articles in DeTelegraaf seem to autocorrelate (Q = 32.60, p = .04). To solve this, the model was extended byincluding another lag, resulting in the VAR model with three lags. This model does not seem tothe problems of autocorrelation in the residuals for Het Financieele Dagblad (Q = 24.89, p = .21), NRC Handelsblad (Q = 15.76, p =.73) and De Telegraaf (Q = 31.38, p =.05). However, thesquared residuals of Het Financieele Dagblad (Q = 82.49, p < .01) and De Telegraaf (Q = 32.39,p =.04) indicate the presence of heteroscedasticity; the squared residuals of NRC Handelsbladdo not reflect heteroscedasticity (Q = 10.61, p = .96). However, besides noting it, I did not payattention to this, but it will be solved with ARCH and GARCH models later in this Dynamic DataAnalysis course.The VAR model with three lags explains more than half of the variation in the number ofarticles per week in Het Financieele Dagblad (R2 = .577) and De Telegraaf (R2 = .558). Theproportion of explained variance of the number of articles per week in NRC Handelsblad is 3
  • somewhat less, though still substantial, because almost a third of the variation is explained (R2 =.316). The estimated impact of the various variables in the model can be found in Table 2. Thevalues in this table can be used to understand the direction of effects, but not to understand theeffects of particular lags on a dependent variable. The values are imprecise and standard errorsare high due to multicollinearity in the VAR model; therefore, we used Granger causalitytesting to inspect the joint statistical significances of the different independent variables (seeTable 3).Table 2. VAR estimates for the 3-lag model of the number of articles in different newspapers Dependent variable Het Financieele Dagblad NRC Handelsblad De TelegraafHet Financieele Dagblad (t-1) 0,32 (-0,04)* 0,11 (0,03)* 0,10 (0,02)*Het Financieele Dagblad (t-2) 0,17 (0,05)* 0,03 (0,03) 0,02 (0,02)Het Financieele Dagblad (t-3) 0,03 (0,04) -0,05 (0,03) 0,05 (0,02)*NRC Handelsblad (t-1) 0,16 (0,07)* 0,23 (0,04)* 0,08 (0,04)*NRC Handelsblad (t-2) -0,07 (0,07) 0,11 (0,04)* -0,01 (0,04)NRC Handelsblad (t-3) 0,05 (0,07) 0,01 (0,04) -0,12 (0,04)*De Telegraaf (t-1) 0,47 (0,08)* 0,08 (0,05) 0,26 (0,04)*De Telegraaf (t-2) 0,03 (0,09) -0,01 (0,05) 0,20 (0,04)*De Telegraaf (t-3) 0,11 (0,08) 0,09 (0,05) 0,09 (0,04)*Climate conventions 0,35 (2,46) 0,71 (1,50) -2,25 (1,28)Constant 4,97 (1,39)* 7,25 (0,85)* 0,86 (0,72)Ljung-Box Q(20) residuals 24.89 15.76 31.38Ljung-Box Q(20) residuals² 82.49* 10.61 32.39*R2 .577 .316 .558Note. Unstandardized coefficients. Standard errors in parentheses; * p<.05To test whether the news coverage about sustainable development in one newspaper Granger-causes news coverage about sustainable development in another newspaper, I look at the test forGranger-causality. It becomes clear that De Telegraaf is Granger-caused by both HetFinancieele Dagblad and NRC Handelsblad; the chi-squared test suggest that excluding thelagged values of Het Financieele Dagblad results in a worse prediction of De Telegraaf (χ2 =35.67, p < .001), the prediction also becomes worse when NRC Handelsblad’s lagged values areexcluded from the model (χ2 = 14.62, p < .01). This substantially means that news coverageabout sustainability in both Het Financieele Dagblad and NRC Handelsblad cause coverage inDe Telegraaf. From Table 2 we can know that these effects will be positive; more newscoverage about sustainability in Financieele Dagblad and NRC Handelsblad will result in morenews coverage about this issue in De Telegraaf. Similar Granger causality effects are found for 4
  • the news coverage of De Telegraaf on Het Financieele Dagblad (χ2 = 42.98, p < .001) and ofcoverage in Het Financieele Dagblad on coverage in NRC Handelsblad (χ2 = 19.10, p < .001);these effects will be positive as can be found in table 2. Two investigated relations betweennewspaper were not significant; news coverage about sustainable development in HetFinancieele Dagblad is not Granger-caused by NRC Handelsblad and news coverage about thisissue in NRC Handelsblad is also not Granger-caused by De Telegraaf. The results of theGranger causality tests indicate that the coverage of not any of the newspapers are exogenous,as they all are Granger-caused by one or two other newspapers.Table 3. Granger causality tests for the number of articles in the different newspapersHypothesid exogenous variable Block coefficients restriced χ2 df pHet Financieele Dagblad NRC Handelsblad 62.998 3 0.098Het Financieele Dagblad De Telegraaf 42.983 3 0.000NRC Handelsblad Het Financieele Dagblad 19.099 3 0.000NRC Handelsblad De Telegraaf 73.269 3 0.062De Telegraaf Het Financieele Dagblad 35.666 3 0.000De Telegraaf NRC Handelsblad 14.615 3 0.002The values of the Granger causality tests do not really help in having a good understanding ofthe different effects. Therefore, impulse response analysis were used, by which it is possible tosee the over-time effects of an unexpected one-unit increase in an independent variable in thefuture values for the dependent variable. Figure 2 shows the different graphs belonging to theimpulse response analysis. It shows a significant and positive effect of De Telegraaf on HetFinancieele Dagblad, which endures the complete period; one week after an unexpected one-article increase in De Telegraaf, an increase of about half an article is found in Het FinancieeleDagblad, this effect decays but still resulted in a quarter article increase after eight weeks. Theeffect of Het Financieele Dagblad on NRC Handelsblad seems smaller; one week after anunexpected one-article increase in Het Financieele Dagblad, about a tenth of an article increasein NRC Handelsblad is expected, this effect drops to zero but does not become insignificant. Asimilar effect is found for the coverage about sustainable development in Het FinancieeleDagblad on coverage about this issue by De Telegraaf. The effect of coverage in NRCHandelsblad on coverage in De Telegraaf is also rather weak, however this effect becomesinsignificant after one week. 5
  • Figure 2. Graphs of the impulse response analysis, title of graph is [impulse variable], [response variable]When the consequences of the effects are added together in a cumulative impulse responseanalysis, it is possible to see what the result was of a one-article increase in a newspaper on theother newspapers’ number of articles about this topic summed together over a period of time(eight weeks in this case). Figure 2 shows the graphs belonging to the cumulative impulseresponse analysis. The graph which displays the cumulative effect of De Telegraaf on HetFinancieele Dagblad, shows that an unexpected one-article increase in this popular newspaperresulted in about three more article in Het Financieele Dagblad after eight weeks. Viceversa, anunexpected increase of one article in Het Financieele Dagblad results after eight weeks in aboutjust one more article in De Telegraaf. About the same was found for the effect of HetFinancieele Dagblad on NRC Handelsblad. The weakness of the effect of NRC Handelsblad onDe Telegraaf also becomes clear in this figure; eight weeks after a one-article increase in NRCHandelsblad this did not led to any increase in the number of articles about sustainabledevelopment in De Telegraaf. 6
  • Figure 3. Graphs of the cumulative impulse response analysis, title of graph is [impulse variable], [response variable]Finally, the decomposition of the Forecast Error Variance is assessed to investigate the effectsof the different variables. The graphs belonging to this decomposition are shown in Figure 4.The decomposition of the Forecast Error Variance determines the impact of one variable’sforecast error on the error in forecasting other variables; it indicates how much of the seriesfuture values cannot be explained due to unexpected shocks in all the different variables in thesystem. After eight weeks for example, 13 percent of the error variance of the number ofarticles about sustainable development in Het Financieele Dagblad can be attributed to shocksin the number of article about this issue in De Telegraaf. Substantially, this means that about atwentieth of the proportion of variance in this number of articles in Het Financieele Dagblad iscaused by variance in De Telegraaf. Remarkable is the relatively large proportion of ForecastError Variance in De Telegraaf that can be attributed to variance in Het Financieele Dagblad;after eight weeks about 33 percent of this error variance of De Telegraaf can be attributed toshock in Het Financieele Dagblad. When the diagonal of Figure 4 is assessed, it is clear that theproportion of error variance that can be attributed to other newspapers is the largest for DeTelegraaf; the error variance of Het Financieele Dagblad and NRC Handelsblad seem to be lessinfluenced by other newspapers. 7
  • Figure 4. Graphs of the decomposition of the Forecast Error Variance, title of graph is [impulse variable], [response variable]ConclusionThe answers on the various research questions are: yes, Het Financieele Dagblad Granger-caused news coverage about sustainable development in both De Telegraaf and NRCHandelsblad; NRC Handelsblad Granger-caused coverage in De Telegraaf, but not in HetFinancieele Dagblad; and De Telegraaf Granger-caused news coverage about sustainabledevelopment in Het Financieele Dagblad, but not in NRC Handelsblad. Based on these findings, I conclude that developments in the economy or business worldattract both the attention of popular media and media with a focus on science. In addition,attention in popular newspapers also causes coverage in business media. On the other hand,coverage in the scientifically oriented NRC Handelsblad did not causes differences in attentionof business newspaper Het Financieele Dagblad, and NRC Handelsblad, for its part, seems notto be influenced by the popular medium De Telegraaf. To extend this discussion: the world ofscience seems thus not to be interested in what the ordinary people think and business peopleare not interested in what science has to offer them. The man in the street on the other hand isinterested in developments of both science and economics, while business people also followwhat ordinary people think is interesting.ReferenceBrandt, P., & Williams, J. T. (2007). Multiple time series models. Thousand Oaks: Sage Publications. 8
  • Do File:*Climate conventionsgen convention=0replace convention=1 if week==43 |week== 44|week==99 |week== 100|week==135|week==136|week== 150|week== 151 |week==201 |week==202 |week==260 |week==261 |week==314 |week==315 |week==365 |week==366 |week==415 |week==416|week==471 |week==472 |week==524 |week==525 |week==578 |week==579replace week = week + 2027tsset week, weeklytwoway (tsline FD, lcolor(red)) (tsline NRC, lcolor(green) lpattern(dash)lwidth(medthick)) (tsline Telegraaf, lcolor(blue) lpattern(dash)lwidth(medium))*Data for FD was double entered in 2006replace FD=FD/2 if week>=2398 & week<=2449twoway (tsline FD, lcolor(red)) (tsline NRC, lcolor(green) lpattern(dash)lwidth(medthick)) (tsline Telegraaf, lcolor(blue) lpattern(dash)lwidth(medium))*with driftdfuller FD*random walkdfuller FD, noconstant*trenddfuller FD, trend*with driftdfuller NRC*random walkdfuller NRC, noconstant*trenddfuller NRC, trend*with driftdfuller Telegraaf*random walkdfuller Telegraaf, noconstant*trenddfuller Telegraaf, trendvarsoc FD NRC Telegraaf, maxlag(8) ex(convention)*two models are prefered: with 2 lags or with 7 lags*Test the VAR model with 2 lagsvar FD NRC Telegraaf, lags(1,2) ex(convention)vargranger*Is an independent variable Granger-causing the dependent variable?When weexclude a variable, does the model get signicantly worse?*df is the number of variables the model gains.predict rv1, resid equation (FD)predict rv2, resid equation (NRC)predict rv3, resid equation (Telegraaf) 9
  • gen rv1_s = rv1* rv1gen rv2_s = rv2* rv2gen rv3_s = rv3* rv3*test for white noise; p>.05wntestq rv1, lags(20)wntestq rv2, lags(20)wntestq rv3, lags(20)wntestq rv1_s, lags(20)wntestq rv2_s, lags(20)wntestq rv3_s, lags(20)*autocorrelation in the residuals of De Telegraaf; so one more lag included*Test the VAR model with 3 lagsvar FD NRC Telegraaf, lags(1,2,3) ex(convention)vargrangerdrop rv1 rv2 rv3drop rv1_s rv2_s rv3_spredict rv1, resid equation (FD)predict rv2, resid equation (NRC)predict rv3, resid equation (Telegraaf)gen rv1_s = rv1* rv1gen rv2_s = rv2* rv2gen rv3_s = rv3* rv3*test for white noise; p>.05wntestq rv1, lags(20)wntestq rv2, lags(20)wntestq rv3, lags(20)wntestq rv1_s, lags(20)wntestq rv2_s, lags(20)wntestq rv3_s, lags(20)* no autocorrelation, heteroscedasticity for FD and Telegraafvar FD NRC Telegraaf, lags(1,2,3) ex(convention)*impulse response analysisirf create cms, set(cms)irf graph irfirf table irfirf table cirfirf graph cirf*Decompositition of forecast varianceirf graph fevdirf table fevd 10