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June 2003
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Contents
Editor's PageAnswers to Three JOE FAQ'sJOE authors often ask me:
My short answers are:
The longer versions (the ones really I give) all have to do with the fact that JOE is a Web journal. Because JOE is a Web journal, I can delay planning an issue until close to the "last minute." This enables me to take as much advantage as possible of article "mix." One of the criteria I use when putting an issue together is how long an article has been in the accepted-for-publication queue, but another is serendipity. In other words, because JOE is a Web journal, I can wait for "lightning to strike." This is one of the advantages of Web publishing (at least from the publisher's perspective). I do notify authors when their articles are being published, but that happens right before the event. So the sooner you send me your revisions, the better. You'll be in the queue, and the arrival of your article might be the serendipitous spark that causes me to see the next issue in a whole new light. And page proofs? They're a paper-journal "ghost." Sending them delays and complicates the publishing process, and, besides, JOE is a Web journal. This means that necessary corrections can be made relatively quickly and easily after an article has been published--something you can't say about paper journals. But realize that JOE is a journal, not a Web site. So we don't update articles or otherwise change their substance ex post facto. But we will correct mistakes that ordinarily would have been caught at a page-proof stage. And authors do occasionally request corrections, which we make when they're justified. Fewer of them are "quibbles," though, and that's another advantage of Web publishing (at least from the editor's perspective). June 2003 JOEWhat an issue. There's a Commentary, "On the Reporting of Response Rates in Extension Research," that all Extension researchers should read and take seriously. It was prompted by "Communicating the Handling of Nonresponse Error in Journal of Extension Research in Brief Articles," which appeared in the December 2002 JOE. These articles raise a critical issue for all of us. If you do have something to say on the subject, don't forget the JOE Discussion Forum, which you can reach at the end of the article. I see the whole world in a blaze of Jungian dialectic, so this I/ENTJ (I'm right on the borderline on the first one) really enjoyed "Decision-Making Styles: An Exploration of Preferences of On- and Off-Campus Faculty." And I've been on enough campus-county teams to believe that the article has quite a salutary take-home message. The last Feature, "Bibliographies as an Extension Outreach Tool: An Old Method in a New Age," and the first Tools of the Trade, "How to Create a Bibliography," are both by the same author, and both suggest that perhaps we should be working more with our librarian colleagues. There's lots of good stuff on 4-H, too, and on technology adoption, and I could go on and on. But I won't. Laura Hoelscher, Editor
On the Reporting of Response Rates in Extension ResearchFrederick Wiseman In a recent Journal of Extension article, Lindner and Wingenbach (2002) presented the results of an investigation into the treatment of non-response error in Research in Brief articles appearing in this journal from 1995 to 1999. One of the conclusions reached was that researchers should report response rates and discuss how potential non-response error was handled because failure to do so brings the validity of survey findings into question. Surveys that have high response rates provide a measure of reassurance that the findings that are obtained can be projected to the population from which the sample was drawn. On the other hand, findings that are obtained in surveys that have low response rates can be questioned because little, if anything, is known about whether non-respondents differ from respondents. During the last quarter century, there has been a general lack of industry-wide standards with respect to the meaning, interpretation, and method of calculation of a survey's response rate. There are numerous reasons for this, including the emergence of more complex sampling and data collection methods that have made the computation of a response rate more difficult. With declining response rates, some researchers have creatively redefined the term to suggest a higher quality data collection effort than was actually the case. As a result, researchers should not only report a response rate as noted by Lindner and Wigenbach, but they should also give the details as to how the rate was calculated. Unfortunately, this is not always done. In such situations, a reported response rate provides little, if any, useful information. Two task forces, one formed in 1982 and the other in 2000, have sought to develop a standardized definition and reporting procedure for the response rate in a survey. This Commentary discusses some of the recommendations that were made by these task forces in an attempt to bring about industry-wide standards. I hope that researchers will adopt the recommendations so that when a response rate is reported, all will know how it is calculated and what it implies. BackgroundThe size of the non-response error in any survey is a function of two factors:
If either a high response rate is achieved or if respondents do not differ from non-respondents, then non-response error is not a problem. In fact, non-response error is only a problem if a low response rate is achieved and respondents differ from non-respondents on one of more of the variables of interest. Because it is difficult to assess whether differences exist between respondents and non-respondents, the response rate (and how it was calculated) should always be reported. Lindner and Wingenbach found that a survey's response rate was reported in 50 out of the 61 surveys that they investigated. The conclusion reached by Lindner and Wigenbach was consistent with the call made 20 years earlier by Miller and Smith (1983). In their article, Miller and Smith noted that the practice of ignoring non-respondents leads many people to question the overall validity of survey research and that non-respondents cannot be ignored if evaluation studies are to have external validity. More recently, Lindner, Murphy and Briers (2001) indicated that steps must be taken to account for possible non-response error whenever a response rate is less than 85%. The problem of non-response is common to all those who conduct surveys, and over the last quarter century, numerous researchers have cautioned about the problem. Smith (1999) provides an excellent review of this literature. For example, in 1978, in response to a request from the National Science Foundation and the American Statistical Association, Bailar and Lampier (1978) sought to determine the extent to which government-funded surveys had met their objectives. They found that due, to a variety of technical flaws, including low response rates, 22 of the 36 surveys that they examined did not accomplish what they had been designed to do. At the same time, members of the US Congress became concerned about the possibility that poor quality survey data were being used for decision-making purposes. The Congress asked the General Accounting Office to determine the likelihood that incorrect or unreliable information was being generated by opinion polls and attitude surveys that were conducted by the federal government. The results of this investigation (Comptroller General of the United States,1978) were similar to those reported by Bailar and Lampier. In addition, with the support of the Marketing Science Institute and CASRO, a trade association whose members are major US public opinion research firms, Wiseman and McDonald (1978) conducted an industry-wide study of non-response in the commercial research sector. They found that, on average, 40% of all selected sample members were never contacted and that approximately one in four sample members who were contacted refused to be interviewed. When these results were presented to the CASRO membership, questions arose as to how response rates should be calculated. There was also disagreement as to the meaning of this term. In response to this, Wiseman and McDonald (1980) conducted another study in which research directors at CASRO firms were surveyed. These research directors were given the response outcomes for three surveys and asked to calculate the response rate in each survey. The data for a telephone survey, in which all selected respondents were eligible to be interviewed, is given in Table 1.
The response rate for this survey that was calculated by each of the research directors in the sample ranged from a low of 12% to a high of 90%. In total, the 40 respondents gave 29 different definitions, with the most frequently reported definition being given only three times. CASRO and AAPOR Task ForcesIn light of these results, the CASRO Board of Directors formed a special task force. This task force had as its principal objective the establishment of a standardized definition and a reporting procedure for survey response rates. The task force, which included representatives from the Bureau of the Census, Office of Management and Budget, commercial research organizations and academia, recommended the following definition (CASRO, 1982):
The task force provided this overall definition for response rate, but noted that in many surveys it would not be possible to determine the eligibility of certain selected reporting units. Thus, certain estimation procedures would be necessary. While the survey research industry wrestled with the problem of non-response in the 1980s and 1990s, it was not until 3 years ago that a major undertaking took place under the auspices of the American Association for Public Opinion Research (AAPOR <http://www.aapor.org/>). This organization, whose membership includes survey research professionals, created a task force to build upon the work of the CASRO task force and to provide the necessary details that had been missing prior to that time. Their report <http://www.aapor.org/pdfs/newstandarddefinitions.pdf> outlined how the response rate should be defined and calculated in various types of surveys. Actually, six alternative response rate formulas and methods of calculation are given because the appropriate formula to use depends, in part, upon what assumptions are made regarding those sample members whose eligibility could not be determined. The task force made the following recommendation (AAPOR, 2000):
The calculation of a response rate in a survey is facilitated by a Response Rate Calculator <http://www.aapor.org/default.asp?page=survey_methods/response_rate_calculator>. This is an Excel spreadsheet, provided by the task force, that calculates a response rate once the researcher provides such data as the number of sample members originally selected, the number of refusals, and the number of sample members not contacted. ConclusionAt the beginning of this Commentary, I mentioned that 50 out of the 61 surveys appearing in Research in Brief articles from 1995 to 1999 reported a response rate. However, in not all instances did the researchers present the details as to how the rate was calculated. I hope that, with the implementation of the CASRO and AAPOR recommendations, a standardization of the reporting of response rates can be achieved and that the response rate for each survey reported in this and in other journals will be calculated and interpreted in a similar fashion. At the same time, attention must also be focused on steps to achieve high response rates and to determine the extent to which respondents differ from non-respondents in sample surveys. ReferencesBailar, B., & Lamphier, M. (1978). Development of survey methods to assess survey practices. Washington, D.C.: American Statistical Association. Council of American Survey Research Organizations. (1982). Special report: On the definition of response rates. Port Jefferson, NY: CASRO. Comptroller General of the United States (1978). Better guidance and controls needed to improve federal surveys of attitudes and opinions. GAO, GGD-78-24. Lindner, J. R., Murphy, T. H., & Briers, G. E. (2001). Handling nonresponse in social science research. Journal of Agricultural Education, 42(4), 43-53. Lindner, J. R., & Wingenbach, G. J. (2002) Communicating the handling of nonresponse error in research in brief articles. Journal of Extension [On-line], 40 (6). Available at: http://www.joe.org/joe/2002december/rb1.shtml Miller, L. E., & Smith, K. L. (1983). Handling nonresponse issues. Journal of Extension [On-line], 21(5). Available at: http://www.joe.org/joe/1983september/83-5-a7.pdf Smith, T. W. (1999). Developing nonresponse standards. International Conference on Nonresponse. Available at: http://www.norc.uchicago.edu/online/nonre.htm The American Association for Public Opinion Research. (2000). Standard definitions: Final dispositions of case codes and outcome rates for surveys. Lenexa, Kansas: AAPOR. Wiseman, F., & McDonald, P. R. (1978). The nonresponse problem in consumer telephone surveys. Cambridge, MA: The Marketing Science Institute. Wiseman, F. & and McDonald, P. R. (1980). Toward the development of industry standards in the reporting of response rates in survey research. Cambridge, MA: The Marketing Science Institute.
Decision-Making Styles: An Exploration of Preferences of On- and Off-Campus FacultyKristine Saunders Tom Gallagher IntroductionOne of the main functions of Cooperative Extension is to facilitate change in our clientele. Field faculty (agents) team up with on-campus faculty (specialists) to develop educational programs that help the public solve problems, improve their lives, and develop sustainable communities. However, communication between on- and off-campus faculty often undermines effectiveness of these programs. The problem has been recognized nationally in Extension. Ukaga et al. (2002) write:
Utah Extension recognized this issue in their state and convened a special task force in 1998 to develop guidelines for successful agent/specialist interaction (Task Force Recommendations, 1998). The report offered guidelines for improvements, including:
From our experience in leadership training, specifically with the Myers-Briggs Type Indicator, we anticipate that these assessments and guidelines, although reasonable, do not get at fundamental differences between on- and off-campus faculty. Although it can be argued that professionals should not need research to work well together, we hypothesize that there are significant differences in decision-making styles between on-campus faculty (specialists) and off-campus faculty (agents). We propose that these differences may give insight into ways to improve communication in decision making, the fundamental activity of client-driven projects. To test this hypothesis we administered a variation of the Myers-Briggs Type Indicator to 127 faculty at Utah State University. We found a significant difference in one dimension of decision-making preferences between on- and off-campus faculty. This difference is closely linked in the literature with communication issues. We suggest that Extension look closely at these differences and initiate training to develop skills among faculty that facilitate communicating effectively across preferences. (We also discovered major differences between faculty preferences and that of the general public, a topic we will save for a second article.) Decision Making and PreferencesField agents work with the public, their clientele, to address issues and make productive decisions. For many issues, agents work with on-campus specialists to bring additional theory and analysis to the discussion about the issue and what to do about it. Whether the agents and specialists use informal or formal research or decision-making model, they deal with such logical steps as:
If agents and specialists differ in how they approach these steps, communication problems can arise. For example, if one faculty member focuses primarily on the problem definition and its human dimensions, while another one is brainstorming alternatives and theoretical constructs, conflict can arise. Part of the rationale for using a structured process in decision making is that it can help individuals with varied preferences complete all the steps (Gallagher, 2002). But how do people differ in their preferences for the various tasks in the process? The mother-daughter team of Myers and Briggs (Myers, 1990), building on the theory of Carl Jung (1923), developed a four-letter code to help people gain insights about themselves. Focusing on the opposites in Jung's theory, preferences can be established for:
MethodsFor this study we used a 70-question variation of the Myers-Briggs Type Indicator (available from the authors on request). We contacted all off-campus agents (78) and all on-campus specialists (49) and asked them to self-administer the test and return the answer sheet by either campus mail or US postal service. Those interested in more information about their type and decision making electronically requested a packet of information. A single reminder was sent 2 weeks after the initial request. ResultsOf the 127 individuals we queried, 84 (66%) responded, including 55 (71%) of off-campus agents and 29 (59%) of the on-campus specialists. In our analysis we first identified the responses of each group for each of the four major preferences, presented in the order used in MBTI training (MBTI Manual, 1994):
We then identified four key pairs of temperaments and used terms applied by Keirsey (1998). There were no significant differences between agents and specialists using these categories.
DiscussionPairs of Preferences Looking first at the results in Table 1, the four pairs of preferences provide insight into the decision-making styles of Extension faculty. Concerning the "where you get your energy", agents are slightly more introverted (I), while specialists are more extraverted (E). The results are not significant, but there is a suggestion that specialists are somewhat more likely to address the problem through an engagement with the outside world, while agents are more likely to use introspection. For the "how you gather information" function, almost all faculty are highly "sensing" (S) oriented, at 93%. Both groups share the preference for gathering information in a literal fashion through their senses. There are relatively few intuitives in the group. For the "how you make decisions" function, there is about an even number of "thinking" and "feeling" preferences for the faculty as a group, but significant differences across the two sub-groups. Sixty percent of agents chose the feeling preference, while 72% of specialists chose thinking. Thus, when most specialists are using rational rules to make decisions, agents are more likely to make decisions based on the values of the people involved. Concerning the "how you live your life" function, the faculty are nearly uniformly "judging" (J) in preference, with 93% for off-campus faculty and 97% for on-campus faculty. Both off- and on-campus faculty are highly oriented toward judging and its decisions/closure preference. From this data we anticipate that there may be some minor problems in communication across the extraversion/introversion (E/I) preference but some major problems across the thinking/feeling (T/F) preference. Temperaments From Table 2, the vast majority (88%) of faculty, agents and specialists, fall into the Guardian category. Several (6) are Idealists and fewer yet (4) are Artisans. There are no Rationals among the Extension faculty. Guardians tend to draw values from the past, to be very concerned about the institution, to desire "the facts," and to focus on "how" rather than "what" and "why." They care about policy, process, and closure. They can be resistant to change, except in small doses that are not threatening. Idealists are often best at drawing values out of people, the affected parties. They are most interested in people data and in alternative futures that benefit people. In the typical group decision process, they can be effective team builders. Artisans, in the decision process, push for action. They like to learn by doing. They are often frustrated by policies and procedures, and strive to get through the decision to the action. They are seldom found in public agencies, avoiding the bureaucracy of hiring and day-to-day work. Rationals come to the decision process with the intention of conducting analysis that leads to logical change. They are interested in the "big picture" and the theory that gives patterns to the data; they love to brainstorm alternatives. Potential for Conflict As noted, over 80% of faculty, both on- and off-campus, are Guardians. However, within this group, the data from Table 1 indicates that there is significant difference between those who prefer "thinking" and those who prefer "feeling" when they make decisions. Thus, there is very high agreement among faculty about the norms of the Guardian, about drawing values from the past, about caring for the institution, and focusing on facts. There is a strong sense of need for policy, process, and closure. Yet, within this broad agreement, there is substantial disagreement about how to get there, about what metric to use--the rational or the feeling--in making decisions. This similarity/difference situation creates a potential for misunderstanding. When there is an implicit assumption that "we are all the same," then the potential to recognize differences may decrease. When differences are expressed in beliefs or behaviors, there can be an increased potential for misattribution, where the meaning is incorrectly interpreted. The Ukaga et al. article (2002) offers specific strategies to work across these differences and avoid misattributions. They include:
The article concludes with encouragement for building a collaborative effort through the power of a shared organizational vision. In Utah, the "guidelines" developed by the taskforce suggest very similar sensibilities and behaviors to work together, with a page of guidelines for agents, a second for specialists, and a third for both. It is our view that these guidelines serve to bridge over differences, but they don't provide insight into why a bridge is needed, into what is creating the divide. That such a divide exists, which requires energy and resources to build and sustain, suggests the value of this type of study about the source of differences. We propose that the first step toward finding these efficiencies is awareness, followed by understanding and skill building through appropriate training. Perhaps ironically, a great many Extension professionals have taken the MBTI. Over two million formal tests are administered nationally each year (Gardner & Martinko, 1996), and experience indicates many are given to Extension faculty. We suggest that the MBTI be revisited for its value in understanding the preferences that agents and specialists bring to decision making, particularly to the "judging" function in which there is much difference. We propose that training in this area is needed to create the awareness, perspective, knowledge, and skills to move toward better communication. We believe that the guidelines offered in the Ukaga et al. article (2002) and by Utah Extension are helpful but not sufficient. It is not our intent to develop guidelines to resolve this gap for Extension. We see the prescription as more long term and propose that a qualified MBTI trainer work with specific groups to understand the situation and the resolution. We see these efforts as targeting the areas of differences raised in the Ukaga et al. article (2002), "...including approaches for determining clientele needs, areas of focus, operational support mechanisms, and procedures for reporting to and evaluation by administrators...", all of which are influenced by decision-making preferences. For those who wish to dig further into this issue on their own, there are several books written about communication across type in the workplace (Kroeger, 1992; Isachsen & Berens, 1995; Hirsh, 1996). ConclusionIn this study we found that Extension faculty have differences, and they are of a type that can influence communication. However, these differences are important not just because they cause communication issues, but because they can lead to both good and bad decision making. On the bad side, the uniformity we discovered suggests that everyone is of the same mind and that there is little room for other perspectives; i.e., in a society where everybody thinks alike, nobody thinks at all. Thus, there may be more agreement, but there is also greater risk of a narrow solution. In this study we found that most faculty have the "sensing" preference, which suggests weak expression of "intuiting," of exploration of possibilities, in decision making. Without the intuitive's high level of creativity and tolerance of change, Extension is likely to be "stuck in a rut"--and some would say it is. On the good side, the differences we discovered suggest a strength. That faculty differ on how to make decisions--"thinking" versus "feeling"--is an asset to Extension because it takes both thinkers and feelers to make a decision that is both analytical and caring. What is needed then is not removal of these differences, but understanding and working with the differences so they become an asset and not a liability. For example, promotion and tenure committees for off-campus agents need to be made up of both agents (F) and specialists (T) so that progress can be reported objectively while recognizing human differences and providing the mentoring and motivation appropriate to the person. One strategy for working with differences is to engage a process that focuses all parties on key steps of decision making:
A final note: Extension faculty in this study are much different, as a group, than the public. With almost 90% of faculty in the SJ category, there appears to be bias toward the Guardian way of management and behavior. This strong perspective can create a culture of norms that dissuades other types from applying for employment or even being engaged in programs. It can make those with different perceptions feel left out of programs and discussions. We are preparing a paper on this subject. To build the interaction and teams that will make Extension successful, Extension needs to create, honor, and work with diversity of people. We encourage more in-depth application of the MBTI to help understand basic differences among faculty, and between faculty and the public. ReferencesBerens, L. V., & D. Nardi. (1999). The 16 sixteen personality types: Descriptions for self-discovery. Telos Publications, Huntington Beach, CA. Gallagher, T. J. (2002). Decision making: An architect's model for Extension application. Journal of Extension [On-line], 40(2) Available at: http://www.joe.org/joe/2002april/tt1.html Gardner, W. L., & M. J. Martinko. 1996. Using the Myers-Briggs Type Indicator to study managers: A literature review and research agenda. Journal of Management 22(1):45-83. Hirsh, S. K. (1996). Work it out: Clues for solving people problems at work. Consulting Psychologists Press, Palo Alto, CA. Isachesen, O., & L. V. Berens. (1995). Working together: A personality-centered approach to management. Institute for Management Development, San Juan Capistrano, CA. Jung, C. G. (1923). Psychological Types. New York: Harcourt, Brace. Keirsey, D. (1998). Please understand me II: Temperament, character, intelligence. Prometheus Book Company, Del Mar, CA. Kroeger, O. (1992). Type talk at work. Dell Publishing, New York. McKenna, J., & Martin, D. (1992). Understanding clientele differences. Journal of Extension [On-line], 30(1). Available at: http://www.joe.org/joe/1992spring/a3.html Myers, I. B. (1990). Gifts differing. Consulting Psychologists Press, Palo Alto, CA. Task Force Recommendations. (1998). Guidelines for successful specialist/agent teams. Unpublished report, Utah State University Extension Service, Logan, Utah. Ukaga, O., M. R. Reichenbach, C. R. Blinn, D. M. Zak, W. D. Hutchinson, & N. J. Hegland. (2002). Building successful campus and field faculty teams. Journal of Extension [On-line], 40(2). Available at: http://www.joe.org/joe/2002april/a3.html
Building a State Child Care Initiative: Applying Principles of Teamwork and CollaborationSusan K. Walker The idea of teamwork and internal collaboration as critical to the future and function of Cooperative Extension has long been promoted. In 1987, Michael Quinn Patton wrote in this journal about the future of Cooperative Extension as making significant contributions in the information age. Rather than providing specialized knowledge, characterized by the needs of an industrial society, he wrote that Extension would best address public issues through "working across program areas, counties, and levels of responsibility in interdisciplinary teams taking a holistic systems perspective." A few years later, Edgar Boone (1990) observed that "Critical issues . . . will require Extension workers in traditional program areas, disciplines and administration to cross lines and function as teams." And in 1996, Arlen Etling advocated teamwork as a principle to help Extension respond to new challenges facing the organization and stay current with the world. Yet each author cautioned that to address critical public issues as teams, Extension would have to confront certain challenges to its organizational culture. Reward and recognition would have to focus on group--not just individual--effort. Skills and motivations of an already overburdened and highly diverse workforce to work collaboratively would need to be addressed. And regarding Extension as a human, integrated educational system, not merely a collection of individuals with technical expertise may require a re-education for current staff. Therefore, before a cross program team approach can be implemented, in some Extension states it will be crucial to first develop factors that help individuals function collaboratively. This article reviews one state's process of developing an internal collaboration, in this case statewide training for child care providers. The educational needs of child care professionals draw from disciplines across family and consumer sciences, including child development, financial management, nutrition, health and safety. Presenting a comprehensive program of continuing education requires a diverse Extension faculty with expertise in the content, experience with the audience, and contacts with a breadth of agency partners. The Maryland experience described here is an example of team building as collaboration, as Kagan (1991) defines it: people working together to achieve common goals that could not be accomplished independently (p.3). More than a coordinated approach to programming, this collaborative effort restructured the expertise and resources of partners (Melaville & Blank, 1993), built an interdependent system to address internal and external needs, and accomplished a shared vision (Bergstrom, et al., 1995). First, the elements of collaboration within an ecological construct (Bronfenbrenner, 1979; Bergstrom, et al., 1995), are discussed to serve as a framework for understanding the necessary steps and intended process and structural outcomes of our experience. Next, the 5-year process toward building an internal collaboration in Maryland is described, followed by an overview of the outcomes achieved related to successful collaborations. Finally, some general insights for team-building within Extension are offered that may be applied broadly to strengthen programming in other cross-program issue areas. Elements of CollaborationCollaborations are built successfully on the relationships between people, and the empowerment of individuals. As Etling observed from organizational management techniques (1996), people are likely to work as a team when they understand the goals and see that the goals of the group fit with their personal needs and goals. They are likely to act when they see a difference and a reward from their actions and make change toward group goals if they can start from what they know and their personal barriers and strengths are addressed. Enabling people to function as a team also means the development of resources, processes, and systems to promote efficient operation and achievement of outcomes. Establishing effective communication systems, providing a mechanism for assessment and feedback, and becoming sustainable are examples of process factors that can enhance collaboration success. Collaborations operate within a variety of contexts that influence their effectiveness. History of working together, the political climate, and catalysts for action are a few examples of contextual factors. The outcomes of the collaboration can be measured in terms of effect on conditions and by actual resource or policy impacts made (for example) that influence those conditions. Building a Child Care Team: One State's ExperienceIn Maryland, childcare center and family childcare professionals must take 12 clock hours of training every 2 years to maintain regulated status (Code of Maryland Regulations, 2001). The state childcare regulatory agency oversees childcare providers and programs; it also approves trainers and training agencies. As an approved training agency since 1994, Maryland Cooperative Extension's (MCE) effort primarily consists of locally held 1 to 2 hour continuing education workshops. These workshops may be offered separately or as part of a day-long conference. MCE has advantages as a statewide system to fill training needs that other agencies and individuals cannot. Most training opportunities are in highly populated, urban areas of the state; MCE's training also reaches rural and suburban providers, in some cases being one of the only sources of continuing training within a county. Tied to the state and national university system, MCE's training also offers connections for research-based content, distance learning opportunities, and extensive topic offerings. Finally, MCE fills a need for the minimally or non-degreed professional who prefers a more informal approach to adult learning and who may be intimidated by college settings (Walker, 2002). Yet, despite these significant contributions, the new state Family Life specialist in 1997 observed MCE's childcare provider training to be in need of coordination, focus, and support. County faculty were largely unaware of what their colleagues were teaching. There was no evident plan for addressing the professional development needs of the childcare provider audience or building an agency system to address those needs. Nor were there identifiable efforts to support or respond to faculty needs. The need to coordinate efforts was voiced by the county faculty and reinforced by the Program Leader. At the same time, there were many internal and contextual assets upon which to build a team effort.
Clearly, in 1997, MCE had strengths to meet critical child care training needs in the state and an opportunity to work more effectively as an integrated system. Year 1: Communicate Statewide Activity A first step toward building the team was to internally communicate about the Extension provider training activity that was happening across the state. Approved trainers in Maryland are required to provide semi-annual (now quarterly) reports of training activity to the state regulatory agency. The reporting requirement was an excellent vehicle to gather information about every county's training activity and report back a statewide picture. Training reports included numbers of providers trained, types of providers (family, center staff, Head Start, etc.), Extension program areas represented in training, agencies collaborated with, and locations of training. These reports became a regular feature and established state to county communication on the statewide effort, and a county to county reporting of individual effort. Year 2. Address Expressed Faculty Needs for Resources FCS faculty desired new, added, and adapted teaching materials for their work with childcare professionals. Yet dollars for the purchase of materials for all counties and specialist time to develop curricula were limited. Two topics important to the provider community that year (1998), that were identified by a statewide survey (Maryland Committee for Children, 1997) but were not currently addressed in the state by Extension, were infant brain development and work and family balance in child care. Partnership with a statewide non-profit agency with funding to develop and disseminate a curriculum for training childcare providers titled "Baby and the Brain" was an easy and inexpensive way to help address the need for resources on the first topic. Later that year, the Family Life Specialist invited an FCS educator to apply for a small award ($1,000) to write a curriculum on work and family balance in child care. The award was received, and by early 1999 "Making Home Work: Work and Family Balance in Family Child Care" (Walker & Barnett, 1999) was ready for training to and use by county Extension faculty. Year 3. Use Coordinated, Regional Events to Pull People Together After 2 years of support and communication, it was time for a significant activity that would bring together the county Extension faculty in a coordinated fashion. MCE applied for and was awarded just under $23,000 by the state Child Care Administration to provide six regional childcare conferences. The conferences involved:
Each regional team had its own marketing plan and conference brochure, and tailored conference aspects to local provider needs. The six conferences reached 483 child care professionals representing 18 of Maryland's 23 counties. Participant evaluations of the conferences revealed them to be popular, of high quality, and effective in stimulating positive change in key aspects of quality child caregiver skill and knowledge (Walker & Morris, 2001). From a team perspective, this statewide activity provided:
Years 4 and 5. Empower Team Members to Create Resources to Meet Organizational Needs The last 2 years have been spent further developing resources for teaching and building processes and structures that are essential for the group to function as team. Early in 2000, the group articulated a mission and prioritized needs to accomplish statewide goals. One of those needs was to develop a standard statewide curriculum for childcare provider training. The most cost-, time-, and resource-efficient solution was for county faculty teams to develop resources. This approach made sense: the educators had been teaching certain topics for several years, had been well trained and supported in the content by Extension specialists, and had materials and resources for teaching at their fingertips. A team approach to developing curriculum materials allowed individuals to coordinate existing content and materials, and package them for statewide use. This also allowed a single specialist to facilitate the development of 12 teaching packages in a year and a half with a budget of $2,000. The 12 topics identified through an assessment with county faculty fit neatly into categories established by the state's new (in 2000) credentialing system based on a Core of Knowledge. Educators fit themselves into topic teams that built upon their existing content expertise. A curriculum committee established lesson plan standards and a timeline for completion. Each lesson plan was to undergo an internal review by a state curriculum team, be externally peer reviewed, and be taught to Extension personnel in the state. Development and training on the lesson plans were completed in November 2002. A second prioritized need identified by the group was for marketing our work so that provider audiences and potential partners could access our services. The group also desired coordinated policies and evaluation strategies to demonstrate statewide effectiveness. Marketing, policy, and evaluation committees were established in 2001. The marketing committee developed a logo that would give us a unique identity (Figure 1). With a budget of $2,500 from an internal program enhancement award, a marketing brochure was created along with a child care activity panel that fit into county FCS program displays. The policy committee has examined common procedures across counties in the delivery of childcare training and is establishing guidelines, for example, on training fees and registration procedures. The evaluation committee is addressing ways to aggregate data statewide, analyze state and local data for practical use, and examine outcomes of the overall child care initiative on Extension personnel, the Extension system in the state, and on the enhancement of child care quality through provider knowledge and skill statewide. Figure 1.
The policy committee has examined common procedures across counties in the delivery of child care training and is establishing guidelines, for example, on training fees and registration procedures. The evaluation committee is addressing ways to aggregate data statewide, analyze state and local data for practical use, and examine outcomes of the overall child care initiative on Extension personnel, the Extension system in the state, and on the enhancement of child care quality through provider knowledge and skill statewide. ResultsMost simply, Maryland's once unfocused, uncoordinated, and unsupported work in child care now operates as an integrated, statewide system of child care provider training and support to trainers. Child care is now recognized by state Extension administrators as a key impact area (University of Maryland, 2002). While to some extent the success of our 5-year experience can be quantified (e.g., we train about 1800 child care providers each year), the prerequisite outcomes of our team-building experience are in the changes in people and processes to function as a collaborative system. These outcomes are summarized below, identified by the process factors that enhance successful collaborations, as noted by Bergstrom and others with the National Network for Collaboration (1995). Documentation for these outcomes is from program reports and evaluations of training activity, recorded comments from county staff, and observations by the Family Life specialist.
With the groundwork laid and the team built, Maryland's child care initiative can take the next steps in completing its mission. We seek to enhance our competencies in child care provider training and meet continuing needs in this field of diverse professionals, in part through offering training at advanced levels and through Internet applications. We aim to maintain (at least) the number of providers that we reach each year, and extend our work to informal caregivers. Insights for Effective Team-BuildingThose who seek to bring together Extension county faculty towards the development of a statewide team effort on a cross-program issue may benefit from the following insights. The Place to Start: Build on the Good Things That Are Present Assets-based planning emphasizes the development of policies and activities based on the capacities, skills, and assets of people involved (Kretzman & McKnight, 1993). Team building can capitalize on existing resources: lots of good minds, years of experience, energy, creativity, interest. The Value of You: Empower and Reward Individuals As Extension systems develop tangible rewards and recognition for teamwork, it is critical for individuals to find personal reward and meaning in the efforts that stimulate collaborative work. When individuals are empowered to see themselves in the vision and plan and future direction, they can feel rewarded by the effort, even if tangible reward is lacking. The county educators' work in child care was continually regarded and was the basis upon which the program was built. They developed their own teaching packages, provided training to their peers, conducted conferences and co-authored evaluation reports. As a result, they have products that can be used to meet individual goals (e.g., promotion and tenure, technological applications, a legacy for years of work). Skill and knowledge has increased, and individuals are motivated and confident in contributing to the team effort. The Power of One: Ensure Trusted Leadership The Family Life specialist took on the leadership role and acted initially as a convener, or catalyst for group change. Bergstrom, et al. (1995) state that this person "must be respected and be viewed as a 'legitimate' player (p. 16)." County faculty needed to depend on the leadership of the specialist if they were going to expend the energy to work more interdependently. This meant trusting communications to be consistent and clear, and seeing her commitment to team members and the mission. The Need to Look and Listen: Be Responsive to Need Each step in building the MCE team was an exercise in responding to the needs of the overall goals of the project while simultaneously responding to the needs, abilities, and interests of the team members. This often required experimentation and improvisation rather than following an established game plan (Etling, 1996). But listening and appropriately responding was the only way to ensure progress of the internal collaborative while it operated synergistically within the larger state and national context of child care professional development. The Need for Help: Seek Resources We found creative, cost-effective ways to produce materials and programs, yet the funding received helped greatly. Nearly $30,000 in internal and external funds to support our efforts has given us a "good credit rating" to attract future funding. These funds helped to facilitate the development of materials and resources for our teaching and the creation of marketing and promotional items and allowed us to better communicate among ourselves and to others. Funding also helped the team feel valued, feel that our work was worth investing in. Taking the time to build a team requires patience and hard work. But, as with any lasting structure, it is essential to start with a strong foundation. ReferencesBergstrom, A., Clark, R., Hogue, T., Iyechad, T., Miller, J., Mullen, S., Perkins, D., Rowe, E., Russell, J., Simon-Brown, V., Slinski, M., Snider, A., & Thurston, F. (1995). Collaboration framework -- addressing community capacity. Fargo, ND: National Network for Collaboration. Available at: http://crs.uvm.edu/nnco/collab/framework.html Boone, E. (1990). Crossing lines. Journal of Extension [On-line], 28(3). Available at: http://www.joe.org/joe/1990fall/tp1.html Bronfenbrenner, U. (1979). The ecology of human development. Experiments by nature and design. Cambridge, MA: Harvard. Code of Maryland Regulations, 07.04.01, [On-line] Family Day Care (10-15-2001). Available at: http://nrc.uchsc.edu/maryland/md_family.htm#pgfId-31885 Etling, A. (1996). Guidelines for change. Journal of Extension [On-line], 34(6). Available at: http://www.joe.org/joe/1996december/tt1.html Kagan, S.L. (1991). United we stand. Collaboration for child care and early education services. New York: Teachers College Press. Kretzman, J., & McKnight, J. (1993). Building communities from the inside out: A path toward finding and mobilizing a community's assets. Chicago: ACTA. Maryland Committee for Children. (1997). Child care training needs assessment. Child Care Issues, June, issue 3. 8-10. Melaville, A., & Blank, M. (1993). Together we can: A guide for crafting a profamily system of education and human services. Washington, D.C.: Center for the Study of Social Policy and the Institute for Educational Leadership. Patton, M. Q. (1987). The Extension organization of the future. Journal of Extension [On-line], 25(1). Available at: http://www.joe.org/joe/1987spring/fut1.html University of Maryland, College of Agriculture and Natural Resources. (2002). Building a stronger Maryland. [Brochure]. College Park, MD: Author. Walker, S. (2002). Predictors of family child care providers' intentions toward professional development. Child and Youth Care Forum, 31(4), 215-231. Walker, S., & Barnett, C. (1999). Making home work: Balancing work and family in family child care. Maryland Cooperative Extension. College Park, MD Walker, S. and Morris, S. (2001). A regional, coordinated approach to Extension child care provider training. The Reporter. 1, 5-10.
Partnerships for Natural Resource Education: Differing Program Needs and Perspectives of Extension Agents and State Agency StaffMartha C. Monroe Susan K. Jacobson Alison Bowers University of Florida The Cooperative Extension Service is respected for its ability to convey science-based information to citizens. The institution is accustomed to updating farmers on the latest in pest research and new seed varieties (Woods, 2002a) or assisting homeowners and communities with horticultural problems. It effectively works in areas where county agents and state specialists have background, information, and experience. Emerging and unfamiliar issues, however, provide a new set of challenges. Partnerships between government agencies and external organizations can synergistically increase staffing, expertise and perspectives to deal more effectively with resource management issues and the public (Endicott, 1993; Rocha & Jacobson, 1998). A partnership for public outreach between the Cooperative Extension Service (CES) and the Florida Division of Forestry (DOF) allowed us to examine this process in the context of wildland fire. This article analyzes what Extension agents and DOF field staff need when communicating to the public about a novel resource management issue and compares their perspectives based on survey results. The findings and recommendations should be helpful when introducing any new topic through Cooperative Extension or when partnering with other agencies. The Florida CES is well equipped to work in agriculture, the state's second largest income producer. The Institute of Food and Agricultural Sciences has a strong history of working with industry to invent frozen orange juice concentrate (Woods, 2002c), conquer tomato yellow leaf curl virus (Woods, 2002b), and reinvent disease-resistant peanuts (Nordlie, 2002). Unlike in other agricultural states, however, information about Florida pests, diseases, crop variants, and climatic concerns are not often relevant throughout the region. The information tends to be Florida-specific. It may not be cost-effective for industries to invest in such limited applications. Thus, the Florida CES and the Florida Agricultural Experiment Station play critical roles in providing farmers and industry with important information to enhance their productivity. This emphasis on agriculture permeates the CES, creating a large group of county agents knowledgeable about plant and animal commodity agricultural issues but less familiar with natural resource concerns. The wildfires in 1998 and 1999 presented a new opportunity for Florida's CES. The fires affected every county in Florida. Many new residents, long-time farmers, condo dwellers, suburbanites, and businesses of many kinds experienced smoke, evacuation, or felt they were at risk of wildland fire (Jacobson, Monroe, & Marynowski, 2001). Even the famous Daytona 500 NASCAR race was cancelled. The economic impact of the 1998 fires was estimated to be at least $620 million (Butry, Mercer, Prestemon, Pye, & Holmes, 2001). In the 13 years since Florida had last experienced a major fire event, the state's population had grown by nearly 4 million people (Florida Research and Economic Database, 2002), many of whom were unfamiliar with the potential flammability of the landscape. Because landowners can help protect their property with vegetation-reduction techniques, appropriate housing materials, and on-going forest and landscape management activities on private as well as public lands (Firewise Web site: <http://www.firewise.org/>), there was and is an important public education role for Cooperative Extension. Pedagogical ContextBarriers to conducting educational programs in the environmental arena are well known. A study of teachers by Ham and Sewing (1987-88) revealed suites of barriers to conducting environmental education. Three main barriers relevant to the development of Extension programs about wildland fire could be:
The basic framework that has supported a wealth of social research in human behavior and behavior change would suggest that in addition to information and positive attitudes, people also require support from peers and supervisors to feel inclined to engage in a new behavior (Hernandez, 2000). The research discussed here investigated opinions among CES and Florida Division of Forestry (DOF) staff 1 year after they participated in an Extension In-Service Training on wildland fire. We examined:
The results helped identify what influenced people to conduct fire programs, what prevented this activity, and compared responses between the two agencies. The Wildland Fire Training ProgramRecognizing that county agents did not have a bank of information about fire to draw from, state specialists worked with other state agencies and organizations to create a toolkit of resources for county agents. With funding from the Advisory Council on Environmental Education of the Florida Fish and Wildlife Conservation Commission, the School of Forest Resources and Conservation (UF) worked with the Florida Division of Forestry (DOF), the Florida Chapter of The Nature Conservancy, and the UF Department of Wildlife Ecology and Conservation to assess public perceptions, write Extension fact sheets, and develop other programmatic resources. The resulting Wildland Fire Education Toolkit (Figure 1) was distributed to county Extension agents, DOF field staff, and county and city fire educators during three 1-day in-service training workshops in January 2000. The workshops provided background information about wildland and prescribed fire, defensible space, and ecosystems at risk and gave participants time to work together to develop a plan to identify at-risk communities, present educational programs, obtain media coverage, and establish demonstration areas. This team approach was designed to help counter any individual perceptions of educational, logistical, or attitudinal barriers. Figure 1.
Extension agents and staff from other agencies were encouraged to work quickly in their counties to conduct programs because the wildfire season started early that year. By May 2000 we had compiled an impressive set of results: 42 programs in 15 counties reached 2,200 citizens; an additional 37 media contacts led to sharing fire messages with a potential audience of 2.1 million residents. Fairs and exhibits drew approximately 23,000 contacts. A closer look at these numbers reveals that Extension agents were not the dominant deliverers of information: 11 were agents (22% of those who attended the in-service training) and 22 were DOF staff (37% of those who attended). An additional 13 other agency personnel (mostly county fire staff) also reported activity in this public education activity. MethodsOne year after the in-service training, a survey was distributed to 104 workshop participants (45 Extension agents and 59 DOF staff) to better understand:
The survey consisted of 9 multi-part questions. One 13-item/5-point Likert scale focused on incentives, knowledge, and attitudes about wildland fire. A 20-item checklist listed possible outreach activities with the Toolkit. A 16-item/5-point rating scale rated possible barriers to conducting programs. And several closed and open-ended items asked for general impressions, improvements, needs, and factors that determine their involvement in public outreach on natural resource topics. A reminder postcard and two subsequent copies of the survey were sent to improve response rate (Dillman, 1978). ResultsA total of 71 surveys were completed and used in the analysis. Several of the non-respondents had moved to a new position, and the survey did not reach them. Phone calls to 10 non-respondents indicated that they have similar perspectives and practices as the respondents, suggesting little non-response bias. The respondents reported that the Toolkit was most useful for conducting public programs (57%), distributing fact sheets (48%), and sending news releases (45%). The least frequent use was for communicating on a list-serv (1%) and for creating flyers (7%). The only significant differences between CES and DOF respondents reflect different strategies that are used to convey information to the public. DOF staff were more likely to be interviewed by the media (x2 = 7.07, p<0.01) and to set up a display at an event (x2 = 7.9, p<0.01). Even the tools that were not frequently used, however, were helpful to some respondents. Although slides and videos were only used by 28% of the agents, over 60% of the respondents rated both tools among the most helpful in another portion of the survey. The diversity of strategies employed by CES agents and DOF staff to convey information about wildland fire indicates that a toolkit with a variety of media is a helpful resource in a partnership. Respondents provided positive comments about the Toolkit in the open-ended section of the survey. They were pleased to have the CD with photographs and requested additional copies of brochures to restock their kits. More videos, more slides, and more presentation outlines were mentioned as helpful additions. The barriers that constrained participants from delivering programs on wildland fire were the same for DOF staff and CES agents. The largest barriers were time to prepare for programs and time to implement programs (rating 3.6 and 3.5 on a 5-point scale where 5 is a very important barrier). Items that have to do with resources, contacts, partners, and local experts were all rated as less important barriers (2.3, 2.2, 1.9, and 1.8, respectively, on the same 5 point scale). A factor analysis (Marradi, 1981) of the barriers reflected these differences by separating the time constraints into one factor and clumping all logistical and resource constraints together on a matrix of five factors. The most important incentives that supported the respondents' use of the Toolkit to educate the public about wildland fire were beliefs that:
Only two (out of 13) items showed a significant difference between CES and DOF respondents. In both cases, DOF staff more strongly agreed that their supervisors believe providing public programs on wildland fire is part of their jobs (x2 = 17.4, p<0.001) and that it was important for their organization to provide public information on wildland fire (x2 = 22.6, p<0.0001). One question asked respondents to reflect on the factors that help determine whether they would provide public programs on other natural resource topics. The most important factors were an expression of interest from the program constituents (4.3 on a 5-point scale) and direction from the ultimate supervisor (3.9 on same scale). CES agents expressed significantly stronger preferences for two factors than their DOF counterparts, namely, (1) expressed interest from constituents (x2 = 12.11; p<0.05) and (2) easily accessible resource people (x2 = 10.14, p<0.05). DOF staff, on the other hand, are more likely to conduct such programs with direction from their ultimate supervisor (x2 = 9.60, p<0.05). DiscussionThe organization of the two institutions, CES and DOF, as well as the agencies' missions help explain the differences in the initial response to using the Toolkit and providing wildland fire programs. The CES is organized from the bottom up; county agents complete their Plan of Work at the end of the previous year to include the activities they will coordinate in the current year. Despite our attempts at marketing the program, few agents were able to drop their previous commitments to design new activities so quickly. The DOF, on the other hand, responds from the top down. If a supervisor tells staff to do fire programs this week, that is indeed what they do. The DOF also has highly visible state authority for wildland fire suppression, so the public and their staff more readily accept their role in fire education. That perception might explain why one County Extension Director was reported to discourage an agent from attending the in-service, because wildland fire was "someone else's job." These differences in organizational structure and perceived responsibility also were seen in the attendance record for the in-service workshop. DOF staff were instructed to attend, so 60 showed up. When the annual voluntary registration period for in-service training closed, only 14 agents were on the list. A memo from the Dean of Extension expressing her expectation that every county send a representative resulted in 42 of the 67 counties attending. In both agencies, people attended the in-service who may not have been initially interested in using the Toolkit. Being forced to attend training may not be the best strategy for building long-term support for a program, but it may also be the only way to begin a novel program in an institution without a track record or publicly expected responsibility in this area. The differences in program activities and motivations reported in the survey results certainly reflect these key differences between the two institutions' responsibilities and structures. Importantly, though, despite these organizational differences, at the individual level there was no significant difference between the two groups in the responses to statements like:
Thus, within the Extension service, agents can accept the fact that wildland fire may not be as important to the mission of the organization, but they may still believe that, in the context of their county and the public they serve, it is an important part of their work. ConclusionNew programs and new issues are difficult to add to the already full plate of county Extension agents. Among the barriers to conducting new programs, logistical barriers (i.e., no program materials, no contacts, no resources) can be reduced by providing a toolkit of program resources and partnering with a relevant agency. The agents and staff who attended an in-service training on wildland fire in 2000 and responded to our survey indicated that the Wildland Fire Toolkit provided needed resources. These resources were useful to both DOF staff and CES agents, even though they have different patterns of working with the public. The distribution of the Toolkit was conducted through an in-service training with a variety of staff, which was an excellent strategy to introduce people to each other and to a new issue. Presumably, this training and the subsequent activity with local partners reduced the educational and attitudinal barriers that might have existed. The most significant barrier, the lack of time, is not something a specialist can easily address. Having the support of supervisors at all levels, however, will assist agents in their justification of why other important programs were given less attention. If a specialist wishes to launch a new program outside the Extension agents' sphere of reference, it may be wise to partner with an agency that has a history or interest in this area. In addition to expanding agents' resources at the local level, a partnership will likely improve immediate use rates. It may take an annual cycle for Extension agents to gain confidence in the new area and build the new topic into their work plan. A partnership is also an important tool to build credibility with the public, both in the creation of the Toolkit and the distribution of the message. Extension may not be the first out of the starting block to deal with novel issues because of organizational design and the plan of work process, but over time, Extension should be as effective as any other agency. The flexibility of agents to utilize new program materials, work with local experts, and adapt programs to meet novel needs on a state-wide basis may make CES a more efficient agency over time. Acknowledgment This research was supported by the Florida Agriculture Experiment Station and approved for publication as Journal series No. R-08706. ReferencesButry, D. T., Mercer, D. E., Prestemon, J. P., Pye, J. M., & Holmes, T. P. (2001). What is the price of catastrophic wildfire? Journal of Forestry, 99 (11): 9-17. Dillman, D. A. (1978). Mail and telephone surveys: The total design method. NY: Wiley-Interscience. Endicott, E. (ed.) (1993). Land conservation through public-private partnerships. Washington D.C.: Island Press. Florida Research and Economic Database. Accessed February 4, 2002. Available at: http://fred.labormarketinfo.com/ Ham, S. H., & Sewing, D. R. (1987-88). Barriers to environmental education, Journal of Environmental Education. 19(2):17-24. Hernandez, O. (2000). Thinking about behavior. In Day, B., & Monroe, M. C.. Environmental education and communication for a sustainable world. Washington DC: Academy for Educational Development. Jacobson, S. J., Monroe, M. C., & Marynowski, S. (2001). Fire at the wildland interface: the influence of experience and mass media on public knowledge, attitudes, and behavioral intentions. Wildlife Society Bulletin, 29(3):929-937. Marradi, A. (1981). Factor analysis as an aid in the formation and refinement of empirically useful concepts. In Jackson, D. J., & Borgatta, E.F. Factor analysis and measurement in sociological research. Beverly Hills, CA: Sage Publications. Nordlie, T. (2002). A+ in agronomy. Impact, University of Florida Institute of Food and Agricultural Sciences. 18(1): 22-24. Rocha, L., & Jacobson, S. K. (1998). Partnerships for conservation: protected areas and non-governmental organizations in Brazil. Wildlife Society Bulletin, 26(4):937-946. Woods, C. (2002a). Award-winning crop management program. Impact, University of Florida Institute of Food and Agricultural Sciences. 18(1):14-16. Woods, C. (2002b). Award-winning rapid response team. Impact, University of Florida Institute of Food and Agricultural Sciences. 18(1):10-11. Woods, C. (2002c). Florida's $9 billion citrus powerhouse. Impact, University of Florida Institute of Food and Agricultural Sciences. 18(1):4-9.
Using Economic Impact Models as an Educational Tool in Community Economic Development Programming: Lessons from Pennsylvania and WisconsinMartin Shields Steven C. Deller IntroductionIn today's complex and volatile economic climate, communities need information to help anticipate and respond to economic change. Local leaders and citizens increasingly face difficult questions about the impacts of changes such as business growth, the decline of traditional industry, and evolving land uses. Increasingly, they are asking how these changes will affect local economic indicators such as employment, income and population, and the demand for public services. To fully understand the effects of economic change, citizens and officials must first understand the local economic structure. Unfortunately, many communities lack the resources to examine the consequences of change. As a result, important decisions too often are made with limited information and understanding and, in some cases, misinformation. Economic impact models can help officials and citizens address these concerns. These models focus on how a local economy functions, how various elements of the local economy are interrelated, and how a change in one element may affect the others. These relationships can help predict important aspects of economic change, including employment and unemployment, commuting and migration, and projected changes in government and school district revenues and spending. University specialists in a number of states (e.g., Pennsylvania, Wisconsin, Missouri, Iowa, Ohio, Minnesota, Texas, and Nevada) are using economic impact models as the foundation of their educational programming. Working under the umbrella of the Community Policy Analysis Network of the Rural Policy Research Institute, this effort has built a national network of community economic modelers. (A detailed overview of RUPRI and the economic modeling effort is available at http://www.rupri.org/cpan/ and in Scott and Johnson [2000].) Extension professionals are using these models with two principal objectives in mind. First, they are used to improve understanding of the economic structure in which decision-makers craft development policy. Second, the models provide practitioners with a tool useful for policy and impact analysis. In this article we describe how we use economic impact modeling in Pennsylvania and Wisconsin to help local residents and officials make more informed decisions. In the next section we describe Extension's historic and expanded roles in economic impact analysis. In the third section we provide a brief description of the basic of economic impact modeling, and in the fourth section we describe a framework in which the models can underscore Extension programming about local economic structure. Finally, we offer some concluding comments. The Evolving Role of Extension in Economic Impact AnalysisExtension has historically responded to requests about the impacts of change in a number of ways, ranging from educated guesses to the application of sophisticated modeling systems. Although educated guesses are often helpful as a staring point, the research-based analyses facilitated by more formal models are generally preferred by most community decision-makers. In fact, over the past 10 years or so, sophisticated, yet flexible, economic impact models have become fairly commonplace, allowing analysts to address and quantify a variety of local economic development issues, including:
While many Extension specialists are facile in these new methods, what is often overlooked is that these questions create a learning opportunity. In economic impact modeling, there are two typical roles Extension can assume when working with communities. The first (and most common) approach is to provide technical assistance in addressing specific questions. Here Extension acts as a quasi-consultant, offering expertise on specific community issues. The second approach returns to the land grant's mission as an educational institution. Here Extension provides educational opportunities for the community to better position itself to improve its own situation. The overriding goal of these efforts is to help communities engage in more informed discussions that lead to better decisions. For smaller and more rural communities, local leaders are often volunteers who lack technical skills for economic analysis. Questions are often not well formulated and commonly reveal a lack of understanding of the economic issues. For these smaller communities, the challenge is to use economic impact models to help leaders and citizens better understand community change. One example of such an opportunity in Wisconsin occurred in 1993, when the Chicago Bears, the professional football team, began renegotiating their contract with the University of Wisconsin-Platteville for the use of the school's facilities for their training camp. The Platteville Chamber of Commerce was concerned that public sentiment would sway the university to look unfavorably on the negotiations. (One must remember that this is Wisconsin, and the Green Bay Packers-Chicago Bears rivalry is taken seriously). The county's Community Development Extension agent was approached by the Chamber to see if the university could document the impacts of the training camp on the local economy. A learning opportunity was at hand. The county educator, working closely with a state specialist, undertook a standard input-output analysis of the tourism event. In the study, concerned citizens, Chamber members, and representatives of the UW-Platteville's Chancellor's Office were all involved. Working closely with the community, discussions about the nature of the study, the required data, and the underlying research methods allowed the county educator numerous opportunities to teach about the economic relationships defining the community. The final release of the study (Lewis & Deller, 1994) drew media attention to the positive economic impact the training camp represented. UW-Extension was able to provide multiple services to the public. Foremost, the research provided direct answers to direct questions. For example, the analysis gave detailed estimates of the number of jobs created, including the spillover effects generated through the economic multiplier process. Here, Extension acted as a technical assistant by providing specific information. The study design also brought the community together to reach a common goal. Assuming the role of a self-help facilitator, UW-Extension was able to help Platteville better understand its local economy and the positive economic benefits of hosting the training camp. In the end, the contracts were re-signed and the Bears' training camp is now a late summer tradition. Overview of Economic Impact AnalysisIn every local economy, businesses, governments, and consumers conduct thousands of seemingly unrelated transactions each day. But from an economic perspective, all of these transactions are interrelated. Businesses sell goods and services to households and other businesses, households sell resources (such as their labor) to businesses, and governments collect taxes from both to pay for public services. Because of these interrelationships, changes in one sector often affect other sectors. For example, when a local business expands, the increase in jobs and income can substantially affect the housing market, the demand for government services, and retail sales, as well as other local businesses. In Pennsylvania and Wisconsin, we apply economic impact models to examine the effects of local economic change. These models, developed from statistical analysis of economic trends, examine the relationships between employment, income, population, and local government and school district revenues and expenditures, among other things. In each of our states, a separate model has been created for each county, using data from the Bureau of Economic Analysis, the Census Bureau, the Bureau of Labor Statistics, as well as state agencies. In addition, these models use the IMPLAN input-output model for part of its analysis. (A complete description of the Pennsylvania model is available at http://cimpsu.aers.psu.edu/.) Central to both the Pennsylvania and Wisconsin models are three major interrelated modules:
Each captures an important aspect of the local economy, and the modules are interrelated, so a change in one will cause changes in the others (Figure 1). Figure 1.
Economic Impact Module This module looks at production relationships among local industries and how changes in the final demand for locally produced goods and services by one business affect other local businesses. For example, if demand for locally produced forest products increases, these businesses will increase their use of inputs (both labor and non-labor) to produce more. Because many of these inputs may be purchased within the community, other local businesses might experience an increased demand for their products. One key result of this module is an estimate of how changes in local business activity affect local employment, earnings and income, both directly and indirectly through the multiplier affect. The production module is built around the widely used IMPLAN (IMpact analysis for PLANning) input-output model <http://www.implan.com/>. Community Demographics Module This module estimates how the studied change affects the population characteristics of a community. If a business creates new jobs, for example, this module | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
