PADM 510 APUS Administrative Theory & Importance of Forecasting Changes and Patterns in Public Relations Paper Where do you see administrative theory inter

PADM 510 APUS Administrative Theory & Importance of Forecasting Changes and Patterns in Public Relations Paper Where do you see administrative theory intersect with: The importance of forecasting changes and patterns in public relations?

This paper will be a case study application of the theories. You must focus your paper on the connection between theories and theorists (attached).

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PADM 510 APUS Administrative Theory & Importance of Forecasting Changes and Patterns in Public Relations Paper Where do you see administrative theory inter
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Prepare a written analysis, generally following the guidelines given below. Your analysis should be approximately 18 pages in length (double spaced exclusive of title page and reference list) and follow proper APA formatting. This paper is intended to applying a theory or set of theories to a practical policy or organizational situation and building a review of literature to back up your analysis.

GUIDELINES:

A major component of this paper will be the review of literature based on the theorists. Each research paper will, of course, be different. However, the central issue in your analysis should be to describe what the case tells us about the theory and practice of public administration. There is no one best way to address this. Thus, as you think about the answer to this primary question, you will need to develop your own framework for answering it. Some general questions that you may want to consider including the following:

What are the issues and why are they issues?
Who are the actors?
What leads the various actors to make the choices or take the positions that they do? What are the personal forces? What are the organizational forces? What are the external forces?
What theoretical perspectives or models help you understand what happened in the case? How?

What does the case tell us concerning;

The nature of the policy system and the policy making process?
The decision making process?
Leadership and management?
Administrative ethics?

In analyzing the case, you should draw upon class readings, peer-reviewed journal articles, legitimate online resources (do not rely on Wikipedia, encyclopedias, dictionaries, or other non-academic sources) as well as personal experiences that may be relevant to your study. Public Organiz Rev (2016) 16:55–75
DOI 10.1007/s11115-014-0296-5
The Failure of Theory to Predict the Way Public Sector
Organisation Responds to its Organisational
Environment and the Need for a Mosaic-View
of Organisational Theory
Bryane Michael & Maja Popov
Published online: 25 November 2014
# Springer Science+Business Media New York 2014
Abstract What does theory predict about the way government size and structure
adapts to changes in government’s organisational environment (particularly to
uncertainty and complexity)? In this paper, we review the theory and evidence
from the literature about the way government size adjusts to such changes –
particularly to changes in macroeconomic fundamentals like gross national product (GDP). We find that the traditional theories from the organisational theory
literature—like the contingency-based view, resource-based view and the rational
choice view – fail to provide global explanations for much of the variation we
see in the world around us. Instead, theorists need to adopt a “mosaic view” of
organisational theory – accepting that different theories may explain the way
public sector size and structure responds to the uncertainty and variability in its
(macroeconomic) organisational environment. We also provide several empirical
hypotheses to test such a mosaic-view.
Keywords Contingency theory . Public sector organisational theory . Resource-based
view . Size of government . Government structure . “Mosaic view”
JELCodes . F4 . D7 . E6 . H1 . H4
The views expressed in this paper remain the views of the authors alone and do not reflect the views of the
organisations for which the authors work or are affiliated with.
The affiliations shown as of time of writing.
B. Michael (*)
Columbia University (SIPA), 420 W 118th St #1, New York, NY 10027, USA
e-mail: bryane.michael@eueconomics.org
M. Popov
General Secretariat of the Government of Serbia, 11 Nemanjina St., Belgrade, Serbia
56
B. Michael, M. Popov
Introduction
Despite over 40 years of theorizing about public sector organisation, we still know very
little about how government responds to changes in its organisational environment. A
variety of theories predict how government size and structure should respond to the
national macroeconomic environment it regulates (as well as buys and sells labour, capital
and goods in). Contingency theorists argue – though are now in relative disrepute – that
government departments and agencies grow, shrink, divide and/or merge in response to
changes in the macroeconomic environment (Gupta et al. 1994). Resource-based theorists
– and their newer off-spring who write about “competencies” – argue that these government departments morph, depending on the resources (budgetary, staffing, know-how and
so forth) they already have available – or can obtain through bureaucratic and/or political
means (Bryson et al. 2007). Rational-choice theorists, and select scholars in public
administration, argue that government organisational structure does (or should)
foresee upcoming challenges and respond to them before they occur (Robertson
et al. 1993 and especially Vietor 2007). Finally, in opposition to these classical
theories, a new school of interpretative and post-modern scholars argue that
government organisational structure reflects cognitive understandings, culture,
politics and symbols which no empirical study can correctly capture – or even
try to (Frumkin and Galaskiewicz 2004). Yet, despite these 40-plus years of
studying public sector organisational theory, most primers about organisational
theory in the public sector contain almost no actual empirical studies proving or
disproving the theories they present (Christensen et al. 2007).
In this paper, we argue for a “mosaic view” of organisational theory – one which
accepts that different organisational theories may apply to different governments’ size and
structure at differing times. By comparing various theories (often from outside the
organisational theory literature), we find that no one theory of organisational theory
sufficiently explains the way all governments respond to their organisational environments over all time periods. Our paper is organised as follows. The first section provides a
basic overview of government sizes and the complexity and variability of the
macroeconomies in which they exist. The section also provides an overview of the proxies
we use to assess the extent to which public sector organisational structure adapts to
changes in its organisational environment. The second section looks at the arguments
and supporting evidence for the contingency-based view of organisational adaptation. We
find that any contingency-based view of such change proves more convincing for some
countries than for others. The third section assesses the extent to which – if governments
do adapt their organisational structure to their macroeconomic environment – they do so
“rationally.” Namely, do they accurately anticipate future macroeconomic changes and
change government organisational structure (using whatever resource available) in anticipation of such change? Or do they observe such changes and adapt reactively – if at all?
The fourth section assesses the extent to which governments adapt their structure based on
the resources (tax revenue) at their disposal, rather than due to changes in the macroeconomic environment. Again, we find that the resource-based view of organisational change
probably fits some countries better than others. The fifth section argues for a “mosaic”
view of public sector organisational theory. In such a view, different theories might apply
to different countries—at different times. We also propose several hypotheses which indepth empirical study could help shed light on. The final section concludes.
A Mosaic-Theory Approach to Public Sector Organisational Theory
57
We would like to point out several caveats and limitations to our discussion before
we begin. First, we discuss the extremely broad concept of “organisational adaption”
using the very narrow definition of government expenditure (as a proxy for
organisational size). We adopt this tactic to keep our paper to the journal’s word limits.
Interested readers can see a much fuller description and discussion of the
various dimensions of public sector organisation in the working paper version
of this paper.1 Second, we do not attempt to deconstruct the vast literature on
the topic – from papers which construct the concept of “organisation” to
extensive reviews of organisational theories. 2 Third, we do not attempt to
review the literature on public sector organisation. 3 Our study sits uncomfortably at the nexus of macroeconomics and organisational theory – as we attempt
to assess how well organisational theory helps us understand public sector
organisation across-borders. As such, we draw from studies outside of
organisational theory—often interpreting them through an organisational theorist
lens.4
What Does Government Size and its Organisational Environment Look Like
Across Countries?
The sizes of governments around the world vary between about 10 % of GDP to over
50 % of GDP. A cursory glance at Fig. 1 shows few similarities between countries
which allow for generalisations about government sizes. Lesotho, the Maldives,
Greece, Hungary and France have some of the largest governments—in terms of the
amount of national resources managed and spent by the government (spending about
twice the world average).5 Academics since Meltzer and Richard (1981) have tried to
explain such differences. Economists like Alesina and Wacziarg (1998) and Rodrik
(1996) have sought explanations—from trade openness to differences in politics. In
truth, academics have given up on such explanations rather than settled on a definitive
one.6
1
Michael and Popov (2011) provide an extended (200-page) working paper version of this paper under the
title The Size and Structure of Government available online. The working paper contains an extended
discussion of size and structure as well as the model and the empirical results we call for in this paper.
2
Much organisational theorising over the recent 10–20 years has exactly argued against attempts like ours to
develop simple definitions and tests of theory. They have sought to incorporate symbolic and interpretive
understandings of organisation – while accepting multiple perspectives (Hatch, 1989).
3
The lack of detailed and rigorous studies in public sector organisational theory may explain why no such
literature review exists to date. Except for Rainey (2009), we know of no broad and wide-reaching literature
review of organisational theories as applied in the public sector context.
4
Roy (2009) provides one of the most obvious examples of a study looking at the issue of changes in
government size to changes in macroeconomic variables from an economist’s perspective. Readers interested
in following this literature can see his excellent overview. Yet, readers steeped in organisational theory (or
macroeconomics) will find our import of economic studies into the organisational theory realm rather
unsettling.
5
We assume, like most authors writing about the size of government, that government expenditure as a
percent of GDP serves as the most relevant indicator of such size. Other measures used in the literature include
employment by the government (at various levels), levels of government consumption, government revenue
(earned through tax and non-tax methods). These other measures of government size correlate highly with
government expenditure.
6
The citations we provide are dated because authors stopped writing about the topic. Durevall and Henrekson
(2011) describe the search for such theorising in their title as a “futile quest.”
58
B. Michael, M. Popov
60%
40%
20%
Biggest 5
interesting middle countries
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Note: The data in the figure show government expenditure as a percent of GDP for 14 “interesting” countries (and a world
average) out of a set of 124 countries for which the IMF provide data. In cases where 2009 data were unavailable, we used
data for the latest year available since 2004.
Source: World Development Indicators (2010).
Fig. 1 Little explains differences in the size of government around the world
Differences in the type and variability of economic shocks in these government’s
organisational environment (as we define it in this paper) may in-part explain differences in government sizes across countries. 7 Figure 2 shows the variability of GDP
over the period 2000–2008 for selected high-income, medium-income and low-income
countries. Low-income countries’ GDP varied more throughout the period than GDPs
in the other income groups. The most volatile economies in the high-income countries
had variances similar to the most volatile economies in the medium-income countries
group. The least volatile economies in all three income groups exhibited very similar
levels of (non)volatility during the period – suggesting that income-level itself makes a
poor predictor of the volatility (and thus uncertainty) of a national economic environment. Authors like Suarez and Rogelio (2005) provide a taxonomy for such change.
Authors likeNaranjo-Gil, David (2009) may take into account actors’ perceived views
of such variability. Yet, volatility still remains the gold standard for measuring change
in any industry or economy.
A more detailed analysis of asymmetric macroeconomic shocks reveals much about
the uncertainty of various governments’ organisational environments. Figure 3 shows
the magnitude and timing of asymmetric shocks (shocks which affect one sector of the
economy rather than the entire economy) for high-income, middle-income and lowincome countries. The figure specifically shows changes in output in the industrial
sector (as a percent of GDP) relative to changes in the service sector and/or the
agricultural sector. The index we show in the figure rises as more resources are drawn
into the industrial sector—and falls as more resources are pulled into the service or
agricultural sectors.
All three income groups have roughly the same magnitude of changes in sectoral
production—albeit at different times. High-income countries tended to have larger
volatility (measured by changes in the change) in industrial output than countries in
the other income classification groups. Medium-income countries tended to have more
7
The canonical definition of an organisational environment from the organizational theory literature defines
such an environment as the “forces outside the boundaries [of the organization] that can impact upon it [the
organization]” (Hatch 2006). In this paper, we focus on the macroeconomic environment and leave out the
other elements such as legal environment, societal, and other environmental factors in order to limit the scope
of our analysis.
A Mosaic-Theory Approach to Public Sector Organisational Theory
59
standard dev. of GDP
9
6
3
medium-income economies
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high-income economies
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low-income economies
The data in the graph show the volatility of GDP between 1999 and 2009 for all countries for which the IMF provide data. We show
examples of countries with the highest and lowest GDP volatility in each income group. We measure such volatility as the standard
deviation of the log of GDP over the period divided by the average log value of GDP during the period. We used the natural log of GDP
(rather than GDP itself) because using log values removes the effect of relvative size (as bigger economies will have a larger volatility of
GDP simply because of their size). Log values – by their nature – describe changes in magnitudes. Thus, by looking at the standard
deviation of the log of GDP, we are focusing on changes in the magnitudes of GDP over the period rather than levels themselves.
Source: World Development Indicators database (2010).
Fig. 2 Different countries have very different economic environments
steady growth rates in industrial output (with far fewer swings in the value of industrial
production). Low income countries tended – in general – to show much less intersectoral macroeconomic volatility than the simple measure of GDP volatility we used
in Fig. 3 above shows. For many low income countries, the size of GDP throughout the
period varied much more than the composition of that GDP between the industrial,
service and agricultural sectors. In all cases, the variance or change in the broader
macroeconomic environment makes the government’s organisational environment
more uncertain – as both government and businesspersons have greater difficulty
deciding to which sector of the economy they should allocate resources.8
Does Government Adjust its Size Contingent on Macroeconomic Change?
How does government size respond to changes in the uncertainty and complexity of the
government’s organisational environment? In the previous section, we showed the
varying degrees to which the organisational environment of various governments
around the world changed during the 2000s. Variance in GDP represents a simple
proxy for the uncertainty and complexity of governments’ organisational environment
(and we will discuss more refined measured later in the paper). More volatility in GDP
makes planning more difficult—thus increasing overall uncertainty (SepulvedaUmanzor 2004). More volatility also likely corresponds with more complex economies
– because more complex economies have a greater need to reallocate resources across
economic sectors, respond quickly and effectively to changes in tastes and technologies
– and so forth.
Changes in government size positively correlate with the uncertainty and complexity
of government’s organisational environment—as measured by the variance of GDP.
8
Indeed, underlying productivity, trade and other factors may affect government while simultaneously
affecting government agencies and departments. For example, an IT innovation (like Facebook) may show
itself as increased volatility in the IT sector. However, the innovation itself may reduce spending on
information collection for certain types of social services (Caliendo et al. 2013).
changes in industrial production
(relative to other industries)
60
B. Michael, M. Popov
40%
30%
low-income countries’
changes in inter-sectoral
output
high-income countries’
changes in inter-sectoral
output
20%
10%
0%
-10%
2000
2001
2002
medium-income countries’
2003
2004
2005
2006
2007
2008
2009
changes in inter-sectoral output
-20%
High Income
Low Income
Middle Income
The figure shows the changes in the relative proportion of GDP in the industrial sector as opposed to in the service sector or the
agricultural sector. We use these changes as a proxy which might show the effects of sector-specific, asymmetric shocks (and
thus measure the overall uncertainty of the macroeconomic environment). We constructed our proxy as follows. We subtracted the
proportion of the service sector in overall GDP from the proportion of industry in overall GDP (giving the absolute change in the
importance of the service and industrial sectors). We divided these differences by the proportion of GDP in the agricultural sector
(thus expressiing all “shocks” relative to the size of the agricultural sector). We calculated the rates of change of these ratios for
each year (removing any rates of change over 300% or -300% which might have popped up due to the country having a relatively
small agricultural sector). We found the arithematic average of these growth rates between 1999 and 2009 and calculated a
weighted average of these growth rates for each of the three groups of countries (high-income, medium-income and low-income).
We used each country’s share of 2004 GDP in current US dollars (as a proportion of the total GDP for that county’s group) as the
weight applied in our weighted average calculation.
Source: World Development Indicators (2010).
Fig. 3 Different profiles of uncertainty in governments’ organisational environment
Figure 4 shows the relationship between the uncertainty and complexity of government’s organisational environment (as measured by average variances in GDP) and
changes in the size of government (as measured by average changes in total government expenditure). 9 For low-income, medium-income and high-income economies,
more output volatility corresponds roughly with more volatility in government expenditure during the 2000s. Such a correlation increases in strength for richer economies.
Low-income economies exhibit a very weak pattern in the data while high-income
economies show a relatively strong correlation between output volatility and the
variance of government expenditure.10 In other words, government size (expenditure)
is contingent on its organisational environment.11
Authors like Kikulis et al. (1995) have observed changes in organisational size and
structure in response to sector-specific changes.12 Yet, we do not observe a relationship
between changes in government size and the magnitude of asymmetric/sector-specific
shocks. The data show—as shown in Fig. 4 – a relationship between the average size of
9
Government spending will affect the macroeconomy – just like changes in the macroeconomy may affect the
size and …
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