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									Is the Cell Phone Associated with
    Perceptions of Government
             Behavior?
         Andy Schaalman
        as0988a@student.american.edu
             American University
         School of International Service
              Research Interest
• The protests of the Arab Spring of 2011 garnered
  worldwide attention for having been coordinated
  principally through information technology couriers and
  social media outlets. In fact, they were just the most
  recent incidents in what has become an ongoing trend of
  public demonstrations for more open and free
  government being organized through these “new media”.
• This pattern of “social media protests” has coincided
  with an explosion in the markets for information
  technology infrastructure and devices in the developing
  world.
            Research Interest
• The device which has seen the most dramatic
  penetration in the developing world in recent
  years is the cell phone; the global mean of
  cellular subscriptions stood at just below 75 per
  100 people in 2008.
• We know from the evidence that information and
  information technology – and by extension, the
  cell phone – have produced greater engagement
  in the behavior of people vis-à-vis their leaders.
  How associated are peoples’ perceptions of their
  leaders and their use of cell phones?
     Corruption Perception Index
• Transparency International: 1995
• Countries are ranked on a 1.0 to 10.0 scale according
  to “the perception of (activities pertaining to)
  corruption in the public sector”, including: bribery of
  public officials, kickbacks in public procurement,
  embezzlement of public funds, and the strength and
  effectiveness of anti-corruption efforts within the
  public sector
• Draws opinions from surveys and assessments of
  businesses and private citizens by renowned
  international organizations (Gallup, Freedom House,
  PriceWaterHouseCoopers, etc.)
  Research Question & Hypothesis
• Research Question:
   – Is the use of cell phones associated with the
     perception of less corrupt (i.e. more transparent)
     government behavior?
• Research hypothesis:
   – Controlling for penetration of the Internet, level
     of political freedom, literacy rate, and GDP per
     capita, I predict there will be a statistically
     significant relationship between a nation’s
     number of cell phone users and its ratings for
     perceived government transparency.
             Background / Lit Review
• Michael W. Collier (Examining Political Corruption):
   – Corruption: social and cultural norms of individual choice and leaders’
     opportunities to exploit them
   – Corruption is reduced and transparency increased when people possess
     the means to maximize their share of the “social surplus”
• Clay Shirky (Political Power of Social Media):
   – “Communications landscape” and penetration of social media have
     provided countries with greater opportunities to strengthen civil society
     and people with more opportunities to unite in common cause
   – No pre-ordained outcomes, but it does give countries the opportunity to
     develop civil society over time
• Jacob Groshek (Multinational Forecasts of Democratic Forecasts
  and Internet Diffusion):
   – Technology provides opportunities, but change is slow; new technology is
     “only as deterministic as the people who create and subsequently use
     them”
   – Early studies (1994-2003) of affects of internet penetration on democracy
     did not produce evidence of association; no causation
                           Data
• Unit of analysis/study : Country
• Source(s) : Transparency International, World Bank
  (World Development Indicators), Freedom House
• Reliability of data:
   – CPI’s basis in perception leaves some opening to
     interpretation
   – About one-third missing data for literacy rate
• Dependent variable:
   – Corruption Perception Index (scale: 1.0-10.0; 1.0 = entirely
     corrupt, 10.0 = entirely transparent)
   – Unit of Measurement = Country
   – LOM = Interval-ratio
Independent and Control Variables
• Independent Variables:
  – Mobile Phones per 100 People
  – Internet Subscribers per 100 People
  – Level of Political Freedom
  – Literacy Rate
  – GDP per Capita

  – All Units = Country, All LOM = Interval-Ratio
Histograms
Histograms
                               Descriptive Statistics
   Variable: (Range)            LOM           Mean           50th      Standard      Observations
                                                          Percentile   Deviation    (Missing Data)
   CPI, 2008 (1.0-10.0)        Interval-   Mean = 3.98       3.2          2.12          169 (0)
                                 Ratio


  Mobile Phones per 100        Interval-   Mean = 74.58      76          45.24          169 (0)
   People, 2008 (1-209)          Ratio



 Internet Subscribers per      Interval-   Mean = 26.89      21          26.30          169 (0)
  100 People, 2008 (1-00)        Ratio



Level of Political Freedom ,   Interval-   Mean = 65.25      63.9        27.26          168 (1)
      2008 (1.0-10.0)            Ratio

Adult (15+) Literacy Rate,     Interval-   Mean = 80.05     87.55        20.15         118 (51)
          2004                   Ratio
 GDP per Capita ($US) ,        Interval-     Mean =         $4,132     $20,025.75       168 (1)
         2008                    Ratio      $13,273.05
CPI vs. Cell Phones per 100 People
                            Linear Regression
                     Single Scatterplot

                 •   N =                 169
                 •   Adjusted r-squared = 0.377
                            = moderate association
                 •   Standard Error =    0.2896
                 •   t =                 0.00286
                 •   SE / t =            10.13 >
                          1.96 = significant
                 •   b =                 1.8286
                 •   t =                 0.2492
                 •   SE / t =            7.34 >
                          1.96 = significant
                 •   Positive, Moderate Significance
                        Bivariate Analysis
Independent Variable Observations      Pearson’s r;
                                    adjusted r-squared     Interpretation    Direction


 Mobile Phones per                                          Reject Ho;
                         169          0.6169; 0.377                          Positive
 100 People, 2008                                        Moderate Strength


Internet Subscribers                                      Reject Ho; High
                         169          0.8514; 0.723                          Positive
per 100 People, 2008                                         Strength

  Level of Political                                        Reject Ho;
                         168          0.6567; 0.431                          Positive
   Freedom, 2008                                         Moderate Strength

                                                         Fail to Reject Ho
 Literacy Rate, 2004     118          0.3216; 0.103                          Positive


                                                          Reject Ho; High
GDP per Capita, 2008     168          0.7885; 0.622                          Positive
                                                             Strength
            CPI      Cell      Internet Political Literacy GDP per
            2008     Phones    per 100 Freedo Rate         Capita
                     per 100            m
CPI         1.0000
2008
            170
Cell        0.6169   1.0000
Phones      0.0000
per 100     169      169
Internet 0.8514      0.7473    1.0000
per 100 0.0000       0.0000
         169         168       169
Political   0.6567   0.4601    0.6004   1.0000
Freedo      0.0000   0.0000    0.0000
m           168      167       167      168
Literacy    0.3216   0.5940    0.5682   0.2084   1.0000
Rate        0.0004   0.0000    0.0000   0.0242
            118      167       117      117      118
GDP per 0.7885       0.5863    0.7766   0.4138   0.3574   1.0000
Capita  0.0000       0.0000    0.0000   0.0000   0.0001
        168          167       167      166      117      168
Matrix Scatterplot
                        Multiple Regression Analysis
                       Dependent Variable is Corruption Perception Index


   Independent
                       Model 1    Model 2    Model 3     Model 4     Model 5   Model 6
    Variables
                         0.029                0.0181                 0.0460
Mobile Phones per
                        (10.13)               (6.54)                 (1.92)
  100 People
                         0.001                 0.001
                                  0.0684                 0.0571                0.0334
Internet Subscribers
                                  (20.98)                (14.79)               (5.52)
   per 100 People
                                   0.001                  0.001                 0.001
                                              0.0372     0.0172      0.0286    0.0188
 Level of Political                           (8.20)      (4.61)     (7.83)    (5.02)
    Freedom                                    0.001      0.001       0.001     0.001

                                                                      0. 603   0. 381
  GDP per Capita                                                      (6.58)   (4.59)
    ($10,000)                                                         0.001    0.001


Adjusted r-squared      0.377      0.723       0.547      0.751       0.748     0.799

 Observations (N)        169        169        167         167         165      165
CPI: Predicted Residuals Values
                    Hypothesis Recap
• Research Hypothesis
   – From a data standpoint, my findings support my research hypothesis: that in a cross-
     national study, use of cell phones is associated with the perceived transparency of
     government. However:
   – Internet subscription a key control factor; still low in most of world
   – Far more data points “low-low” and close to slope on scatterplot
   – The most consistent indicator across a variety of multiple regression models is still
     political freedom.
   – These trends suggest – as Shirky and Groshek argue – that the diffusion of technology
     alone cannot bring more transparent government; the proper elements of civil society
     must be in place first.
      Policy Implications #1
The connection between rate of cell phone use and
perceptions of government behavior – individually
and as one component of the information technology
dynamic – is apparent. However, as the scatterplot of
the basic linear regression and the multiple regression
models show, there is more association between low
CPI ratings (high corruption) and low cell phone use
than between high ratings and high use. This means
that the spread of the device has been so swift –
especially relative to population internet access – that
it has created a large bloc of countries where a
discernible gap exists between the “mobile
connectivity” of people and the balance of “social
surplus” between the people and the government.
Where Phones Exceed Transparency: 2008 Data
                      Cell Phones
      Country        per 100 People
                                      CPI

       Philippines        75          2.3

        Moldova           67          2.9

          Iran            60          2.3

         Libya            77          2.6

         Russia           141         2.1

         Egypt            51*         2.8

         Mean            74.58        3.98

         50th %           76          3.2
         Policy Implications #2
The recent protests in Egypt, Iran, China, Myanmar, and
elsewhere speak to this gap: the governments there
were not less corrupt than before – the people just had
the opportunity and the means to coordinate together to
air grievances in large numbers (and to varying degrees
of success). In these countries and others like them, the
development of civil society sufficient to keep corruption
(and the perception of such behavior) in check has been
outpaced by the march of technology.
With this in mind, US policymakers should heed the
advice of Shirky and Gorshek and focus on fostering
growth of civil society from the ground up in the
developing world, instead of spending large sums for
“access and connectivity” in efforts to spring civil society
up overnight.
                Policy Implications #3
•   The United States and its international partners should remain committed
    to promoting information freedom and the spread of new technology in
    all its forms, but must adjust to each individual case and focus on specific
    commitments rather than making holistic commitments and investments
    to countries that are “undeveloped” or “censored”.

Examples:
1. Iran – work to debug “phone trackers” used by Revolutionary Guard
2. Afghanistan – assure mobile banking system kept to Afghan National
    Police until assurance of security provided
3. Africa – delay proposed initiative on mobile investments until current
    humanitarian efforts contribute to civil society growth
4. Myanmar – conflict mediation and civil society promotion first priority
5. “Freedom” bills – put aside and let diplomats do their jobs
                                          Sources
•   Theresa Thompson and Anwar Shah, Transparency International’s Corruption Perceptions Index: Whose
    Perceptions are they Anyway? Worldbank.org
    http://siteresources.worldbank.org/PSGLP/Resources/ShahThompsonTransparencyinternationalCPI.pdf
•   Michael W. Collier, Examining Political Corruption. Columbia International Affairs Online
    http://www.ciaonet.org/isa/com01/
•   Clay Shirky, The Political Power of Social Media: Technology, the Public Sphere, and Political Change.
    Foreign Affairs Magazine, Jan/Feb 2011 http://www.foreignaffairs.com/articles/67038/clay-shirky/the-
    political-power-of-social-media
•   Dan Rice and Guy Filippelli, “One Cell Phone at a Time: Countering Corruption in Afghanistan”. Small Wars
    Journal, 2010 http://smallwarsjournal.com/blog/journal/docs-temp/527-rice.pdf
•   Jacob Groshek, A Time-Series, Multinational Analysis of Democratic Forecasts and Internet Diffusion.
    http://ijoc.org/ojs/index.php/ijoc/article/view/495/392
•   Mark Landler and Brian Knowlton, “U.S. Policy to Address Internet Freedom”. New York Times, 2/14/11
    http://www.nytimes.com/2011/02/15/world/15clinton.html
•   “Use Mobile Phone Banking to Share Africa Resource Wealth: World Bank”. China Post, 6/10/11
    http://www.chinapost.com.tw/business/africa/2011/06/10/305611/Use-mobile.htm
•   Transparency International online
•   World Bank, World Development Indicators online
•   Freedom House online

								
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