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2011 Housing Planning Study - Technical Report
ence.Beyond Information. Intelligence. 5 Established 1960 Database Marketing Economic&Social Impact Studies Evaluations Research Modeling/Forecasting HAWAVI HOUSING PLANNING STUDY, 2011 TECHNICAL REPORT SMS Prepared for the: 1042 Fort Street Mall Suite 200 Hawaii Housing Finance and Development Honolulu, HI -3356 96813 Corporation and Housing Officers/Administrators for Ph:(808)537-3356 p g Toll Free(877)535-5767 Honolulu, Maui, Hawaii, and Kauai Counties Fax:(808)537-2686 E-mail:info @smshawaii.com Website: www.smshawaii.com SMS Affiliations and Associations: Experian International Survey Research Solutions Pacific,LLC Prepared by .' Research & Marketing Services, Inc. SMS Consulting, LLC November, 2011 3i Marketing&Communications CONTENTS INTRODUCTION.......................................................................................................................................1 PROJECTSTRUCTURE................................................................................................................................1 HOUSING INVENTORY REPORT.........................................................................................................3 RENTAL HOUSING REPORT................................................................................................................4 HOUSING DEMAND SURVEY...............................................................................................................6 METHODS..................................................................................................................................................6 DATA TABULATIONS...........................................................................................................................11 HAWAII HOUSING MODEL...............................................................................................................12 HOUSINGMODEL 2011 ...........................................................................................................................12 MODEL CHANGES FOR 2011....................................................................................................................15 APPENDIX................................................................................................................................................17 APPENDIX 1: HOUSING DEMAND SURVEY INSTRUMENT.......................................................................18 Hawaii Housing Planning Study,2011: Technical Report Page i 0 SMS, Inc. November,2011 LIST OF TABLES TABLE 1. DEMAND SURVEY SAMPLE RESULTS,2011..................................................................................8 LIST OF FIGURES FIGURE A-1. HAwAI'I TMK ZONES,2011 ...................................................................................................5 Hawaii Housing Planning Study,2011: Technical Report Page ii 0 SMS, Inc. November,2011 INTRODUCTION The objective of the Hawaii Housing Planning Study (HHPS) 2011 was to add new and timely information to that gathered in previous studies and to continue the development of the Study as a comprehensive housing planning tool. In past Housing Policy Studies, results have slowly evolved toward the latter goal. The original housing study in 1992 produced the first comprehensive set of data related to housing issues in Hawaii. The 1997 study updated that information, and added an analysis of rental housing costs in the State. In 2000, a set of items selected from the Housing Demand Survey of 1997 was administered to a large sample of Hawaii households in order to help in reconciling HHPS data and Census estimates. The 2003 Study updated the information once again and added an evaluation of the housing needs of the elderly, the risk of homelessness in Hawaii households, and two surveys to examine awareness of and interest in the Section 8 Housing Voucher Program. In 2006, the Study was expanded to include an analysis of housing production data over the last five years and the housing model was radically restructured in response to the needs of housing analysts in Hawaii. The 2011 HHPS shifted focus from providing the multitude of data tables included in previous studies to examining the policy and planning implications of the Study's findings. PROJECT STRUCTURE The HHPS 2011 utilizes data from six data collection and analysis sources: 1. Housing Stock Inventory: An inventory of all housing units in the State at the end of 2010. In 2011, the inventory was expanded to include U.S. Decennial Census data and data taken from the American Community Survey (ACS)'. Inventory data are the foundation for counting and describing housing stock and are fundamental to the Hawaii Housing Model. 2. Rental Housing Study: A study of rental unit advertisements, prices, and characteristics from January 2006 through May 2011. The rent study was expanded this year to include data from the ACS, the Office of Housing and Urban Development's (HUD) Fair Market Rents, and other sources. 3. Production Data: A set of interviews with housing producers to enhance understanding of issues related to housing development and a review of County data on scheduled housing unit production aimed at developing reliable estimates of short-run housing production. 4. Housing for Special Needs Groups Study: This study included a set of stakeholder interviews with persons who work with special needs groups and understand their housing needs, as well as hard data on the special needs populations, including their numbers, housing needs, available housing units, and future prospects. 5. Housing Demand Survey: A statewide survey of more than 5,000 households to measure current housing conditions, expectations to move to a new unit, new unit preferences, financial qualifications for purchase or rent, and demographic characteristics of household members. For those unfamiliar with the American Community Survey, an excellent description appears on the U.S. Census website http://www.census.gov/acs/www/about the survey/american community survey/ Hawaii Housing Planning Study,2011: Technical Report Page 1 0 SMS, Inc. November,2011 6. Hawaii Housing Model: Updates made to the HHPS model included Hawaii housing conditions, prices, and sales, permit forecasting of housing unit needs by income group through the year 2030. Each of these project elements is described in detail in the HHPS 2011 Technical Report. In 2011, the study team also reviewed housing plans and production, government spending on housing, and comparisons with housing data in other states and municipalities. In the following pages, these project elements are discussed in greater detail. Results of the HHPS 2011 are reported in the document entitled Hawaii Housing Policy Study, 2011, and several short reports on special topics including the Rental Housing Report, Housing Stock Inventory Report, and the Housing of Native Hawaiians Report 2 2 In addition, multiple data tabulations have been supplied to individual agencies under separate covers. Hawaii Housing Planning Study,2011: Technical Report Page 2 0 SMS, Inc. November,2011 HOUSING INVENTORY REPORT An extensive analysis of Hawaii's existing housing stock was performed to provide a comprehensive data set and to identify housing production patterns. A database was developed from a number of sources including the Department of Revenue and Taxation database, Department of Land Management data, residential real estate property management companies, military housing producers, and Hawaii's various universities, community colleges and resident high schools. The project analyzed over 500,000 single family, multi-family and apartment residential units. Six distinct housing types have been summarized — single family3, condominium°, apartments, military, student housings, and cooperative 7. The data describe total inventory for the year ending 2010. Where they are identified, vacation rentals and units otherwise unavailable to the local housing market have been eliminated from the inventory. Not all multi-family units converted to visitor accommodations, and not all single-family units converted to bed-and- breakfasts, are known. As a result, the inventory may include a limited number of these types of units. Property characteristics such as land area, living area, number of bedrooms, year built, tenure, and owner- or tenant-occupied were compiled and analyzed. The information has been summarized for the State as a whole, and for each County. 3 Includes detached units intended for single family occupancy. Excludes single family units under the condominium ownership regime. 4 Includes all housing units registered under a condominium ownership regime, whether single family detached, or mufti-family attached units. 5 Includes all non-condominium, non-cooperative multi-family units, apartments, multiplex, duplex, etc. 6 Student housing or dormitories were added to the TMK inventory from reports by educational institutions of the number of units they currently operate. Units intended for faculty use are included here. 7 Includes all multi-family apartments that are owned as cooperatives. Hawaii Housing Planning Study,2011: Technical Report Page 3 0 SMS, Inc. November,2011 RENTAL HOUSING REPORT In order to evaluate the condition of Hawaii's rental housing market, a comprehensive data set was constructed to identify current and historical rental availability, rental rates and other trends. For each island, information including the location, rent rate, number of bedrooms and property type was assembled from rental advertisements for each island. A three-period rolling average of rent rate was used in reporting rent data in order to reduce the volatility of the rent data series. Data reported include advertisements published through the end of 20106 The data presented in this report reflect only market rental rates; no affordable (subsidized) rents have been included except where published in classified advertisements. Database entries also exclude rentals wanted, vacation rentals, rentals to share, property management, rooms for rent, and all commercial properties. Rental area definitions were created using the standard Tax Map Key (TMK) Zones for each county and the rental databases have been categorized according to these geographic locations. Refer to Figure A-1 on the following page for maps of the TMK Zone boundaries. Not all areas depicted on the maps have corresponding rental data included in the report due to the extremely limited number of published rental advertisements for these areas. However, data for these areas is included in countywide averages. The Oahu rental database was collected from the Honolulu Advertiser's mid-month Sunday classified advertisements for rentals of houses, apartments (including both apartment building units and condominium units) and townhouses. For the purposes of this review, the Oahu rental database was filtered to include advertisements for three- and four-bedroom houses and studio, one-, two-, and three-bedroom apartments. The Neighbor Island rental database was constructed from the mid-month Sunday classified ads from the major newspapers for each island. Sources include the Maui News, West Hawaii Todav, the Hawaii Tribune Herald and The Garden Island. The database contains information from advertisements for two-, three-, and four-bedroom houses and studio, one- and two-bedroom apartments. In addition, from the Maui News, studio and one-bedroom houses were categorized together as "cottage" since they constitute a significant part of Maui's rental market. 8 Data from the first half of 2011 was not included because the need to generate moving averages requires a full year of data in order to generate appropriate comparisons. Data associated with the charts is provided as a separate Excel file. Hawari Housing Planning Study,2011: Technical Report Page 4 0 SMS, Inc. November,2011 Figure A-1. Hawaii TMK Zones, 2011 County Zone Area Name 41 Waimea 42 Koloa Kauai q;1 44 45 Lihue Kawaihau Hanalei Ulu PUC Honolulu Shore O'ahu County Zone Area Name 31 Puna 32 South Hilo Maui 33 North Hilo 34 Hamakua Hawaii 35 North Kohala 36 Kohala Coast 37 Kailua-Kona 38 39 South Kona Kau County Zone Area Name 21 East Maui 22 Upcountry Maui 23 Central Maui 24 West Maui 25 Molokai 3 4 2 1 c w Hawaii Housing Planning Study, 2011: Technical Report Page 5 ©SMS, Inc. November,2011 HOUSING DEMAND SURVEY This study was conducted as an update to the Hawaii Housing Policy Study, 2006. The research design was developed to match past survey content, sampling method, data collection and data processing procedures as closely as possible. There were several important differences initiated for the 2011 study: (1) the survey content was streamlined and the instrument was a bit shorter than in previous years; (2) the sample was considerably larger than in 1992 and 1997, and somewhat more complex in design; and (3) additional measures were included to evaluate risk of homelessness, elderly housing needs and issues related to rail transit. METHODS SMS Research designed the survey instrument with input from the Hawaii Housing Finance and Development Corporation (HHFDC), County Housing Agencies, the Department of Hawaiian Home Lands, and private sector housing interests across the state. The reviewers suggested several changes in content, and most of those changes were incorporated in the final survey instrument. The final version of the survey instrument is shown in the Appendix A. Each County was divided into several sub-areas for the survey. These geographic survey areas may not correspond exactly to those used in previous iterations of the HHPS, but are very similar. The sample sizes for the geographic subdivisions survey were sufficient to produce results that are statistically accurate within plus-or-minus five percentage points at the 95 percent confidence level. Thirty pre-test surveys were conducted among Hawaii households using the same methodology as were employed for the actual survey. The purpose of the pre-test was to determine whether survey items were understandable to the general public, included the most appropriate response options, and were arranged in the proper order for effective inquiry. Some minor changes to the survey content were made as a result of the pretest. These are reflected in the survey instrument as shown in the Appendix. Sampling The target population for this survey included all residents of the State of Hawaii residing in non-institutionalized housing units with working telephone service at the time of the study. The sample design was a dual frame design in which independent samples are selected from two different sampling frames representing the same population. In this case the two frames were the list of Iandline telephone numbers active at the time of the survey and the list of wireless telephone (cell phone) number active in Hawaii at the same time. Two independent samples with identical designs were selected, one from each frame. The samples were both random digit dialing (RDD), disproportionate across geographic area and random within areas. In the case of the Iandline sample, independent samples were selected for each of the required geographic areas (see below). The frame was the SMS RDD sample Hawaii Housing Planning Study,2011: Technical Report Page 6 0 SMS, Inc. November,2011 selection system which permits disproportionate sampling by telephone exchange. A similar system has been developed for wireless telephone numbers. The landline sampling frame was stratified by geography comparable to districts selected by each county agency participating in the study. Districts differed from one county to another. There were five districts on the Hawaii Island (Ka'u/South Kona, North Kona, North Hawai i, North and South Hilo, Puna), Oahu (Leeward Oahu, Central Oahu, Windward Oahu, PUC Honolulu, East Honolulu) and Ka'ua'i (Waimea, Koloa, Lihue, Kawaihau, Hanalei). Maui County had the largest number of districts with six on the island of Maui (Nana, Makawao/Pukalani/Kula, Paia/Haiku, Kihei/Makena, Wailuku/Kahului, West Maui) and one each for Molokai and Lanai. The wireless sampling frame was stratified by county only. At the present time, this frame cannot be meaningfully stratified at any lower level. The address associated with each number is taken from the location of the retail company that sold the phone and/or plan being used with each number. Internal survey data are then used to locate the user address according to the same areas noted above. The disproportionate samples were designed to produce equal sampling precision for these districts. The number of households in each district in 2011 was estimated by SMS Research and sample sizes were selected to produce standard errors of the proportion of plus-or-minus five percentage points at the 95 percent confidence level, with p = .50. The sample design is shown in Table 1 on the following page. Interviewer Selection and Training SMS Research was responsible for the selection, training, and supervision of all interviewers assigned to this project. Regardless of background or experience, all interviewers were specially trained to conduct the housing survey interviews. The training session included: a review of general telephone interviewing procedures; a question-by-question review of the survey instrument; on-screen CATI training; and a question-and-answer session to make sure that interviewers had all problems handled before beginning work on the survey. During the fielding of the survey, there were frequent, short debriefing sessions in which interviewers could bring up any additional questions or issues and have them addressed by the project manager. Data Collection Survey data were collected by phone from March through August 2011. All interviews were conducted from the SMS Honolulu Calling Center and separate calling protocols were developed for Iandline and wireless surveys. The Calling Center is equipped with a state-of-the- art computer assisted telephone interviewing (CATI) system that was used for this project. The system provides for rigorous control of sampling, disposition of all calls dialed, and survey administration. It works equally well for Iandline and wireless calling, but the call disposition codes are set differently for each survey type. Calls were placed between the hours of 12:00 PM and 9:00 PM on weekdays and 10:00 AM and 9:00 PM on weekends. An unlimited callback procedure was employed. In practice, some numbers were re-dialed as many as eight times in order to complete interviews. SMS conducted a follow up mailing to areas of Maui County (Nana, Pa'ia-Haiku, West Maui, and Lanai) to supplement areas in which we were able to reach quota for the telephone surveys. Surveying took place during September 2011. A total of 344 surveys were returned from those areas. Hawaii Housing Planning Study,2011: Technical Report Page 7 0 SMS, Inc. November,2011 A professional supervisor was present at all times during the fielding process and a call monitor was responsible for monitoring calls. Interviews were monitored on a rotating basis through the CATI system and neither the interviewer nor the caller is aware that monitoring is taking place. Monitors follow the course of the interview and watch the choices being recorded as the respondent answers. If any deviation from procedures is noted, the call monitor conducts a short re-training session with the interviewer to assure that inter-coder reliability is maintained. Table 1. Demand Survey Sam Ie Results, 2011 Household Sample Modes Households Sample Margin a 2010 Size of Error Landline Cellphone Mail ITota 449,360 5,554 1.31 3,936 976 y&Co untyof Honolulu 292,003 1,111 2.93 907 204 -- Primary Urban Center 130,196 227 6.50 157 70 -- Central Oahu 77,668 249 6.20 187 62 -- East Honolulu 13,753 195 6.97 183 12 -- Leeward 29,310 219 6.60 189 30 -- Windward 41,076 221 6.57 191 30 -- County of Hawaii 54,644 1,299 2.69 1,115 184 -- South Kona-Kau 4,249 210 6.59 190 20 -- Puna 11,506 330 5.32 295 35 -- North &South Hilo 18,091 340 5.26 284 56 -- North Hawaii 8,726 211 6.66 178 33 -- North Kona 12,073 208 6.74 168 40 -- County of Maui 43,687 2,106 2.08 1,127 337 642 Island of Maui 40,223 1,620 2.39 874 315 431 Hana 593 111 8.39 61 2 48 Makawao, Kula 9,296 291 5.65 232 59 -- Wailuku-Kahului 12,832 277 5.82 174 103 -- Paia-Haiku 3,819 328 5.17 141 31 156 Kihei-Makena 7,572 213 6.62 156 57 -- West Maui 6,111 400 4,74 110 63 227 Island of Molokai 2,305 205 6.53 193 12 -- Island of lanai 1,160 281 5.09 60 10 211 Kauai 20,460 1,038 2.96 787 251 -- North Kauai 8,837 408 4.74 301 107 -- Kawaihau 6,374 252 6.05 181 71 -- Hanalei 2,463 156 7.60 120 36 -- Lihue 4,057 194 6.87 133 61 -- Waimea, Koloa 7,567 436 4.56 353 83 -- Waimea 5,566 235 6.26 195 40 -- Koloa 2,001 201 6.56 158 43 -- Hawai i Housing Planning Study,2011: Technical Report Page 8 0 SMS, Inc. November,2011 Data Processing The CATI system is programmed to conduct certain types of data editing as the interview is being conducted. Out-of-range codes are not allowed and contingencies are enforced. Following the fielding process, data files are reviewed and edited for internal consistency and other possible errors that may have passed the automatic editing routines. Edited data are then coded by professional staff who assign numeric codes to open-ended items, and sort and check verbatim responses. Weighting and Balancing of Demand Survey Data An analysis was conducted to identify any serious non-response bias in the demand survey data and the check for mode effects between the Iandline and cell phone surveys. It was determined that there was no need to statistically adjust for mode effects. Disproportionate coverage for several demographic variables was noted, especially in the cell phone surveys. Following the procedures developed by The Centers for Disease Control for the Behavioral Risk Factors Surveillance System, with some adaptations based on system applied at Pew Research, SMS has developed a weighting system for dual frame sample surveys in Hawaii. The weighting has three components as shown below. 1. Sample Weights: The disproportionate sample design assured equal precision by district, but resulted in an unbalanced sample by district. Sample weights are designed to statistically adjust survey results for a disproportionate design by weighting survey results to the distribution of the populations form which the sample was drawn. Weights were constructed by dividing the population estimates by the sample counts on a cell-by- cell basis. This procedure is the same as the weighing procedure used in previous Housing Policy Study Demand Surveys. 2. Sample Raking: The weighting scheme for the housing demand survey in 2011 must also account for dual frame sampling (a difference in telephone service available to each household) and the heavier non-sampling error associated with two-frame sample surveys involving cell phones. Since the exact number of households by type of phone services, household size, home ownership, age and gender of respondents, etc., is unknown, the standard methods of poststratification (statistical adjustment for non- sample error) will not work. The solution is to use one of several methods of sample balancing, or raking as it is better known these days. The method begins with sample weighs applied as noted above, and then balances the sample for type of phone service (Iandline only, Iandline mostly, wireless mostly, wireless only, and no phone service). In the same procedure survey data are simultaneously balanced for disproportionality in other raking variables including: age of respondent, household size and type, homeownership, marital status, and households with and without children under the age of 18. 3. Replicated Weights: Replication-based weights have been developed to adjust for variance distortion resulting from to complex sample designs. They are required to adjust sample variances used for statistical tests and certain forms of multivariate analysis. Using the replicated weights, users can estimate standard errors for simple estimators like totals or complicated ones like logistic regression parameter estimates. Hawaii Housing Planning Study,2011: Technical Report Page 9 0 SMS, Inc. November,2011 Sample weights and raked weights were applied in all tabulations developed for and all analyses conducted based on demand survey data. This weighting was necessary to statistically adjust housing demand survey so that the data accurately represent the number of households by district, the size of household, number of children in the household, unit tenure, marital status, age of respondent, as well as landline and cell phone usage. Hawaii Housing Planning Study,2011: Technical Report Page 10 0 SMS, Inc. November,2011 DATA TABULATIONS A. Comparison of 1992, 1997, 2003, 2006 and 2011 Housing Demand Survey data. The data on current housing conditions, preferences for new units, qualifications for ownership and rental, and demographic characteristics of households were collected in the same manner in all three years. Results are also reported in the same format. With few exceptions, it is possible to compare results for 1992, 1997, 2003, 2006 and 2011 in great detail. The full range of comparisons will require comparing data in this report with the tabulations in The Hawaii Housing Policy Study, 1992, The Hawaii Housing Policy Update, 1997, The Hawaii Housing Policy Update, 2003 and The Hawaii Housing Policy Update, 2006. The 1997 report also produced summary tables of the most important information in the study. This year's report provides those tables for 1992, 1997, 2003, 2006 and 2011. Data include: 1. Housing unit condition 2. Housing costs for current units 3. Household composition and crowding 4. Shelter-to-income ratios 5. Intention to move 6. Tenancy preferences 7. Housing unit preferences for renters and buyers 8. Preferred locations of new units for owners and renters 9. Affordable housing costs for new units 10. Financial profiles of potential buyers and renters in all counties 11. Interest in sustainable housing B. 2011 survey results by County. This subsection presents the 2011 demand survey results for the state as a whole and for each of the four counties. In general, the material on current housing conditions is presented first, followed by housing preferences. The affordability data is next, and the final tables present demographic characteristics of survey respondents. C. 2011 survey results for districts within counties. This subsection presents the same data as described above, separately for each county. Within each county's section, demand survey results are shown for the following geographic districts: Honolulu: Primary Urban Center, Central Oahu, East Honolulu, Leeward Oahu, and Windward Oahu Maui: Hana, Makawao-Pukalani-Kula, Paia-Haiku, Kihei-Makena, Wailuku-Kahului, West Maui, Lanai, Molokai Hawaii: South Kona to Ka'u (census tracts 212, 213), Puna (census tracts 210, 211), North and South Hilo (census tracts 201-209, 221), North Hawaii (Hamakua, North and South Kohala) (census tracts 217-220), North Kona (census tracts 214-216) Ka'ua'i: Waimea, Koloa, Lihue, Kawaihau, Hanalei Hawaii Housing Planning Study,2011: Technical Report Page 11 0 SMS, Inc. November,2011 HAWAII HOUSING MODEL From the start, the Hawaii Housing Planning Study has included a model of Hawaii's housing market intended to summarize the findings of the study and support estimates of current demand and forecasts of unit needs into the future. The model has become a central focus of the study over the years and has been updated each time the study was conducted. As housing planners became familiar with each new model their expectations grew. By 2003 it was apparent that the original model structure was insufficient to answer the growing number of questions planners put forth and some structural changes were made. In 2006, it was decided to maintain the basic structure developed in 2003 and to significantly redesign the model and its outputs. In 2011, the Request for Proposal (RFP) for the project called for no changes to the Hawaii Housing Model. HOUSING MODEL 2011 The Hawaii Housing Model for 2006 is the base of housing modeling in the State of Hawaii today. It will be useful to review its basic composition here. The model combines information from the housing inventory and housing demand surveys with basic population and economic series in a multi-faceted model designed to simulate the structure of Hawaii's housing market and to produce a forecast of housing units needed through the year 2030. Foundation Data The foundation variables for the Hawaii Housing Model are the population of Hawaii (taken from DBEDT and Census estimates) and the number of housing units in the State (taken from the Housing Inventory). Several important data series round out the foundation data: + ➢ Total housing units in the State; single family and multi-family units ➢ Market rent data for single family and multi-family units, including: • Percent of households that rent • Number of single family and multi-family rental monthly ads (supply) • Median single family and multi-family rents (value) ➢ Single family and multi-family new construction estimates ➢ Affordability calculated from HUD income guidelines each year for each county ➢ Visitor unit estimates, including: • New construction • Units that enter visitor plant (used as hotel rooms) • Units lost to visitor industry (when tourism is strong) ➢ Housing resale estimates for single family and multi-family units, including: • Number of units on market • Excess inventory • Number of resales All of the data series listed above are gathered for each county. The Hawaii Housing Model can be used to develop estimates for the State as a whole or for each individual County. SMS updates these data periodically, regardless of the HHPS schedule. Hawaii Housing Planning Study,2011: Technical Report Page 12 0 SMS, Inc. November,2011 Important Calculations Several important variables from the Hawaii Housing Model are calculated internally and checked against external sources. The procedure provides for smooth and reliable forecasts. The newly calculated variables include: ➢ Affordability Ratios: The ratio of the housing price affordable to a household with a median family income to the median sales price in a given year. ➢ Population and Households: Estimates are now for the housed population only, and for the empirical number of households in the State. In the past, the number of households was calculated by dividing population by the average household size. The new estimate is a more accurate indication of household formation. ➢ Vacancy Rates: Vacancy rates for past models were a blanket estimate of five percent per year. The new model uses empirical estimates of vacancies in each county. ➢ Household Income: Household income is a new addition to the model. ➢ Prices and Sales: Formerly, housing prices and sales were gathered for separate sources. New Model Structure Before 2006 the Hawaii Housing Model was a relatively straightforward population model. It assumed that the demand for new housing units was a linear function of the number of people in Hawaii and the number of housing units. Modules were developed to estimate the number of households from raw population estimates and the number of housing units available to the resident market from housing inventories and estimated numbers of units withheld from the market. The different between the two was calculated as a surplus or deficit in housing units available to the resident housing market. The redevelopment accomplished in 2006 produced a supply and demand model. It simulates the effects of income and affordability on supply and demand and on prices, rents, etc., based on past market performance. The model is driven by affordability ratios that change in response to supply (the availability of units affordable to buyers in different income categories) and demand (the change in number of households and household income). Functionality The Hawaii Housing Model is a dynamic model that allows for several types of what-if analysis. The model was designed to be user-friendly, and allows the user to customize numerous parameters. Safeguards are built into the model to assure that important data are not compromised by user manipulations. Three types or levels of user manipulations are available. 1. Parameters Changes: The model features an easy-to-use set of interactive drop-down menus for conducting what-if analysis by changing the values of model parameters such as income growth rates, population growth rates, interest rates, and new construction. Users may change one or more parameters and re-estimate the model. The Hawaii Housing Planning Study,2011: Technical Report Page 13 0 SMS, Inc. November,2011 programming code itself cannot be affected by these parameter changes and users need not worry about damaging the model software. 2. Customizable Parameters: The more experienced user may wish to change entire sets of parameters such as household income, population, interest rates, or new construction. For this set of operations, entire sets of data, which combine starting levels, growth rates and growth curves are available to the user to change as needed. This procedure requires some brief training, but provides substantial latitude for developing model solutions to fit client needs. 3. Model Changes or Additions: Users with more knowledge of programming may wish to make substantial changes to the model design or add capacity or functionality to the model itself. Most users will want to contact SMS for this kind of work. For those who wish to try it themselves, unlocked versions of the model are available to Consortium members. Unlike previous models, the new Hawaii Housing Model provides a more comprehensive forecasting ability. It is possible, for instance, to use the model to estimate what the next housing price run-up will look like. Although the model is not designed to predict exactly what will happen and when, it shows a rough approximation of what supply and demand forces do to the housing market. The new model also comes with a caveat. Like all forecasting models, future projections depend heavily on the past behavior of the key data series -- the Hawaii housing market. Since the early eighties, Hawaii's housing market has witnessed three price run-ups, interspersed with adjustment periods. It is quite likely, then, that any manipulation of the model parameters may change the shape and character of the next priced run up, but will not eliminate them as features of the market trend. There are no data to suggest that a run-up will not occur in the future, or that the next run-up will not be followed by an adjustment period. Technical Specifications The Hawaii Housing Model was developed using Microsoft ExcelTM. The decision was made in 1997 by Consortium members to forego migrating to more complex modeling languages in order to assure that the model could be operated by a broad range of planners using commonly available hardware and software. Although this imposes some limitations on functionality, it seems worth the price. The model is available to all members of the Consortium and requires a standard PC with at least 2.0 gigs of RAM and about 30 Megs of storage space. Of course the user would need a reasonably recent version of Excel. The model was built up from a set of custom built user-defined functions (macros) in Excel. This allows for more complexity and options in the calculations. The specifics of the calculations will not be described here, but the calculations simulate the effects of inputs on supply and demand, prices, and affordability. The model also simulates the conditions that cause a price run-up, like the one that occurred from 2003-2006, and the effects of the run-up. Hawaii Housing Planning Study,2011: Technical Report Page 14 0 SMS, Inc. November,2011 MODEL CHANGES FOR 2011 As requested by users, no major changes were made to the Hawaii Housing Model in 2011. There were changes made to the data. Most of these were required because of advances in data collection and reporting between 2005 and 2011. All of those changes provided more data and more accurate data for use in the model. Employing them, however, required some major manipulations of some data series and some minor changes in programming. For those who are interested in these niceties, we discuss them briefly below. Readers who are interested in learning even more about these issues can contact Jim Dannemiller at SMS. Rental Prices, 2005 to 2011 This topic has been covered in greater detail in another report in the HHPS 2011 series. The fundamental issue is that the rental housing study, which has always been based on capturing newspaper advertisements on Hawaii rentals, has been recently compromised. The rental advertising trade is rapidly moving from print media to the Internet. Those who are engaged measuring rental advertising have not yet been able to develop systems to accurately reflect the market. Their efforts are continuing and program may be made from the next study. In the meantime, the Census Bureau has begun to include a question on recent rent prices (and recent home purchase prices) in the American Community Survey. This may be an excellent source of information in the future, but is a new effort in 2011 that has not been adequately tested. Other sources of rental price information are available, especially the HUD measurement of Fair Market Rents (FMR). But these too have definitional problems that compromise their utility for use in the Housing Model. For 2011, we have forecast the past rental prices based on the rate of change in FMR. The 2010 level is currently based on a combination of estimates from the old rental studies and the 2009 ACS. We will update to the 2010 census numbers as they become available. Housing Unit Counts, 2000 to 2011 This is another topic that has been covered in a separate report in the HHPS 2011 series. The issue is that the Housing Inventory, based on review of TMK records, does not coincide with figures on housing units and housing typos supplied by the Census and ACS. The problem is being approached by several agencies in Hawaii and will be resolved within the next year or so. For the current Model we have built in the 2010 Census data where possible as an anchor. The pathway from past Inventory made through the last half of the decade has been straight-lined from 2006 to 2011. Other New Data Series Several other pieces of data have proved to be problematic in the updating of the housing model for this report. We list them briefly below. Those who are interested in further detail may contact the authors. Hawaii Housing Planning Study, 2011: Technical Report Page 15 ©SMS, Inc. November,2011 Housing vacancy rates are now available in greater detail and for all counties in the Census and the ACS. Data users are familiar with the impact of ACS on their work and the problems involved with acquiring this new, more detailed, and more timely set of data. ACS is a survey, with all of the accompanying variance issues, especially for areas with smaller sample sizes. Perhaps more important, ACS data do not seem to match the 2010 Census data and that causes all of us some concern. These issues can and will be worked out, but it takes time to acquire the larger samples sizes required for that work. When the vacancy rate data "settles down", the ACS and census combined data will be the data we need for analysis and modeling of Hawaii's housing market. For the 2011 housing model, we used to Census and ACS data, modeling them to fit the previous data series. "Snowbird Units" is a series that is important to estimating needed units in Hawaii because those units are lost to the local housing market but appear in counts of total housing units. In the 2010 census, the Bureau includes the definition (and counts) for housing units defined as "vacant, resident lives elsewhere". This is certainly the best estimate we have seen so far for what we sometimes call "snowbird units". The dividing line between snowbird units and other vacant units is now well defined. Population and Households are also problematic when using ACS data. Here, the population growth trend seems reasonable and accurate, but the year-to-year fluctuations in the data are more likely the result of sample variation than actual changes in population. For many applications this does not present a serious problem, but the fluctuations affect forecasting routines in important ways, and cause dramatic changes in housing predictions. For the 2011 model we use the Census estimates and smoothed the estimates between 2005 and 2010. Doubling Up and Crowding are two more variables that are better measured in 2011 than they have been in the past. In this case, it occurs without serious drawbacks. The crowding indices are defined in the same way that have been in the past and are no routinely available by year and county. The doubling-up variable, however, is still one for which we must rely on the HHPS Demand Survey data. The Housing Policy Study 2011 also brought to light information that will likely change the housing model significantly in the next several years. The data on homelessness, hidden homelessness, and at-risk of homelessness will be more valuable in the future. More and more, homelessness is seen as a housing problem. With respect to housing policy, it has never been possible to ignore the important role of homelessness in funding housing initiatives. As homelessness becomes understood as an integral result of the working of the housing market in Hawaii, it will be more important to include it in the housing model. The same might be said for the problems of persons with special needs. It would seem that housing is a central need of this important subpopulation. The likelihood is that they will be included in Hawaii housing policy and planning in more meaningful ways in the futures. And if that is so, we might expect to hear the call that their data be included in the Housing Model. Everyone who took part in the study this year look forward to those challenges. Hawaii Housing Planning Study,2011: Technical Report Page 16 0 SMS, Inc. November,2011 APPENDIX Hawaii Housing Planning Study,2011: Technical Report Page 17 0 SMS, Inc. November,2011 APPENDIX 1: HOUSING DEMAND SURVEY INSTRUMENT 17 - Other 0.1 Hello, I'm with SMS Research, a 99- Don't Know/Refused Honolulu research company. We are conducting a survey about housing in Hawaii. 0.7 Are you or anyone in your household at least The results will be used to plan for housing 25% Hawaiian? needs in the State. Are you an adult resident 1 -Yes of Hawaii? Are you one of the heads of the 2 - No household? 9— Refused Q.2 Please be aware that my supervisor may be Q•8 Are you a DHHL applicant on the waiting list taping this interview for internal quality for Hawaiian Homestead land? control. 1 -Yes 2 - No Q.3 We would like to begin by asking you a few 8- Don't Know questions to determine what we will ask you 9— Refused during the survey. First, what was your age at your last birthday? Q.9 Is anyone else in your household on the 1 - Under 18 years DHHL waiting list for Hawaiian Homestead 2 - 18 to 21 land? 3 - 22 to 34 1 -Yes 4 - 35 to 59 2 - No 5 - 60 to 74 8- Don't Know 6 - 75 or older 9— Refused 9— Refused you current) live on? Q•10 Are you a DHHL Lessee? Q.4 What island do y y 1 -Yes 1 - Oahu 2 - No 2 - Maui 8- Don't Know 3 - Hawai'i 9— Refused 4 - Ka'ua'i 5 - Moloka'i Q.11 Are you living on Hawaiian Homestead land 6 - Lana'i right now? 9- Refused 1 -Yes 2 - No Q.5 What is your current zip code? 8- Don't Know 9— Refused Q.6 What is your ethnic background? 01 - Caucasian Q.12 Are you a part of DHHL's Undivided Interest 02 - Black or African-American Group who are lessee's soon to be awarded 03 - Hawaiian or Part-Hawaiian their land? 04 - Japanese 1 -Yes 05 - Chinese 2 - No 06 - Filipino 8- Don't Know 07 - Korean 9— Refused 08 - Vietnamese Q.13 Thank you. Next, I have some questions 09 - Asian Indian about your current home. How many bedrooms are 10 - Other Asian there in your home? 11 - Guamanian or Chamorro NUMBER OF BEDROOMS: 12 - Micronesian, Chuukese, etc. 13 - Samoan Q.14 How many bathrooms are there in your 14 - Other Pacific Islander home? 15 - American Indian or Alaska Native NUMBER OF BATHROOMS: 16 - Hispanic or Latino Hawaii Housing Planning Study, 2011: Technical Report Page 18 ©SMS, Inc. November, 2011 Q.15 How many other rooms in your home? 03 - $500 to $799 THE FOLLOWING ROOMS DO NOT 04 - $800 to $1,099 COUNT: 05 - $1,100 to $1,399 • utility rooms -washer/dryer room 06 - $1,400 to $1,699 • pantry 07 - $1,700 to $1,999 • hallways 08 - $2,000 to $3,000 • foyer 09 - Over $3,000 • gallery 10 - Already paid for • Lanai 99- Don't Know/Refused • breezeway NUMBER OF "OTHER" ROOMS: Q.21 What is your best estimate of the market value for your additional properties? This Q.16 Is your home a single-family house, a includes the cost of the land and the home. townhouse, a condo, or an apartment? 1 - Less than $150,000 01 - Single family house 2 - $150,000 to $200,000 02 - Townhouse 3 - $200,000 to $250,000 03 - Condominium 4 - $250,000 to $350,000 04 - Duplex/multiplex 5 - $350,000 to $500,000 05 - Apartment 6 - $500,000 to $1 million 06 - Co-op 7 - More than $1 million 07 - OTHER 9- Don't Know/Refused 08- Don't Know 4.22 How much is the total monthly rent for your Q.17 Do you own or rent your home? home, including any utility payments, 1 - Own maintenance fees or parking? Is it... 2 - Rent 01 - Less than $200 3 - Occupy without payment 02 - $200 to $499 4 - Homeless 03 - $500 to $799 9- Refused 04 - $800 to $1,099 05 - $1,100 to $1,399 Q. 18 Do you own any other types of investment 06 - $1,400 to $1,699 or primary properties? 07 - $1,700 to $1,999 1 -Yes 08 - $2,000 to $3,000 2 - No 09 - Over $3,000 8- Don't Know 10 - Already paid for 9- Refused 99- Don't Know/Refused Q.19 What is your best estimate of the market Q•23 Do you live in public housing? value for your primary property? This includes the 1 -Yes cost of the land and the home. 2 - No 1 - Less than $150,000 8- Not Sure 2 - $150,000 to $200,000 9- Refused 3 - $200,000 to $250,000 4 - $250,000 to $350,000 Q•24 Do you receive Section 8 assistance? 1 -Yes 5 - $350,000 to $500,000 2 - No 6 - $500,000 to $1 million 7 - More than $1 million 8- Not Sure 9- Don't Know/Refused 9- Refused Q.20 How much is the total monthly mortgage for Q•25 For the following questions, the word "home" your home, including any utility payments, means any type of home - either a house, maintenance fees or parking? Is it... condo, apartment or townhouse. About how 01 - Less than $200 old is your home? If you're unsure of the 02 - $200 to $499 Hawaii Housing Planning Study,2011: Technical Report Page 19 0 SMS, Inc. November,2011 exact age, would you be able to give us an estimate of the year it was built? Q.32 When you do move, do you expect to stay NUMBER OF YEARS: on the same island, move to a different island, or move out of the state? Q.26 What year was your home built? Was it... 1 - Stay on same island 01 - Prior to 1950 2 - Move to different island 02 - 1950 to 1959 3 - Out of state 03 - 1960 to 1969 8- Don't Know 04 - 1970 to 1979 05 - 1980 to 1989 Q.33 What island would you move to? 06 - 1990 to 1999 1 - Oahu 07 - 2000 to 2009 2 - Maui 08 - 2010 or newer 3 - Hawai'i 88- Don't Know 4 - Ka'ua'i 5 - Moloka'i Q.27 Do you think it is. . . 6 - Lana'i 1 - Less than 10 years old 8- Not Sure yet 2 - 10 to 20 years old 9- Refused 3 - Or more than 20 8- Don't Know Q.34 What are the major reasons that you will be moving out of Hawaii? Q.28 How long have you lived in your current 1 - Mentioned housing as a reason home? 2 - Did not mention housing Days 8- Don't Know Weeks Months Q.35 Do you think you will be buying or renting Years your next home? 1 - Buying Q.29 Would you say that your home is large 2 - Renting enough for the number of people living 3 - Moving in with relative, friends there? 4 - OTHER 1 -Yes 8- Don't Know 2 - No 8- Don't Know Q.36 Are you pretty certain that you will buy, or do you think you might rent, instead? Q.30 Would you say that the physical condition of 1 - Sure to buy your home is... 2 - Might rent 1 - Excellent 8- Don't Know 2 - Satisfactory 3 - Fair Q.37 What are the main reasons you won't buy a 4 - Or poor? place? 8- Don't Know 01 - Too expensive 02 - Won't stay long enough Q.31 When is the soonest that you would probably 03 - Don't want to buy, prefer rent move to another home? 04 - It's up to someone else 01 - Less than 6 months 05 - Might buy, but probably not 02 - 6 months to a year 06 - Can't afford down payment 03 - 1 to 2 years 07 - Don't want to be tied down 04 - 3 years 08 - Can't qualify for loan 05 - 4 to 5 years 09 - Can't afford monthly payment 06 - 6 to 10 years 10 - Worried about job security 07 - Over 10 years 11 - Think market is bad now 08 - Probably never 12 - OTHER 88- Don't Know 88- Don't Know Hawaii Housing Planning Study, 2011: Technical Report Page 20 ©SMS, Inc. November, 2011 11 - $15,000 to $17,499 Q.38 Would you consider renting an affordable 12 - $17,500 to $19,999 housing unit provided by DHHL? 13 - $20,000 or more 1 -Yes 88- Don't Know 2 - No 99- Refused 8- Don't Know Q.44 About how much do you think you would be Q.39 Do you intend to buy a home later on in the able to pay as a down payment? Include future? money from relatives, or from the equity in 1 -Yes property you would sell. 2 - No 01 - None 8- Don't Know 02 - Less than $5,000 03 - $5,000 to $14,999 Q.40 In approximately how many years do you 04 - $15,000 to $24,999 expect to buy a home? 05 - $25,000 to $39,999 06 - $40,000 to $59,999 07 - $60,000 to $99,999 Q.41 If there were currently homes available that 08 - $100,000 or more you could afford, would you want to buy 88- Don't Know one? 1 -Yes Q.45 About how much would you be able to afford 2 - No to pay each month for all housing costs if you buy a 8- Don't Know home? 9- Refused 01 - Less than $200 02 - $200 to $499 Q.42 About how much can you afford to pay each 03 - $500 to $799 month for all housing costs, including rent, 04 - $800 to $1,099 utilities, maintenance fees, and parking? 05 - $1,100 to $1,399 06 - $1,400 to $1,699 01 - Less than $200 07 - $1,700 to $1,999 02 - $200 to $499 08 - $2,000 to $2,999 03 - $500 to $799 09 - $3,000 to $3,999 04 - $800 to $1,099 10 - $4,000 or more 05 - $1,100 to $1,399 99- Don't Know/Refused 06 - $1,400 to $1,699 07 - $1,700 to $1,999 Q.46 Would you be most likely to move to a single 08 - $2,000 to $2,499 family house, a townhouse, or a condo? 09 - $2,500 to $2,999 1 - Single family home 10 - $3,000 or more 2 - Townhouse 99- Don't Know/Refused 3 - Condo 4 - Other Q.43 About how much money do you have in 8- Don't Know savings or other sources of money that you 9- Refused could use for a down payment? 01 - Less than $500 Q.47 The next home you move to -- Would that 02 - $500 to $999 most likely be a single family house, a 03 - $1,000 to $1,999 townhouse, a condo, or an apartment? 04 - $2,000 to $2,999 1 - Single family home 05 - $3,000 to $3,999 2 - Townhouse 06 - $4,000 to $4,999 3 - Condo 07 - $5,000 to $7,499 4 - Apartment 08 - $7,500 to $9,999 5 - Other 09 - $10,000 to $12,499 8- Don't Know 10 - $12,500 to $14,999 9- Refused Hawaii Housing Planning Study,2011: Technical Report Page 21 0 SMS, Inc. November,2011 Q.54 What is the smallest size house you would Q.48 If you can't find a house in your price range be willing to live in? for monthly rent, would you be willing to 01 - About 800 square feet move to a townhouse or condo? 02 - 800 to 999 square feet 03 - 1,000 to 1,199 square feet 1 -Yes 04 - 1,200 to 1,499 square feet 2 - No 05 - 1,500 to 1,999 square feet 8- Don't Know 06 - 2,000 or more square feet 07 - None of the above; I'd prefer a multi- Q.49 If you had your choice, in what area would family unit you live? Probe: Are there any other areas 08- Don't Know you prefer? 09- Refused Q.50 How many bedrooms would you like to have Q.55 Is there any need for any of the following in your new home? features in your next home? 1 - None - studio 1 - Ramps 2 - One 2 - Railings 3 - Two 3 - Wheelchair modifications 4 - Three 4 - Bathroom grab bars 5 - Four 5 - Shower seat 6 - Five or more 6 - Emergency call device (to summon help) 8- Don't Know 7 — None of these 9— Refused Q.51 What is the smallest number of bedrooms you can live with? Q.56 Do you need these features for someone 1 - One over the age of 60? 2 - Two 3 - Three 1 -Yes 4 - Four 2 - Depends 5 - Five or more 3 - No 8- Don't Know 8- Don't Know Q.52 How many bathrooms would you like to have Q.57 Next, we have a few more questions about in your new home? your future home. Would you consider 01 - One buying a housing unit with features 02 - One and one-half designed to meet the needs of senior 03 - Two citizens? 04 - Two and one-half 05 - Three 1 -Yes 06 - Three and one-half 2 - Depends 07 - Four or more 3 - No 08- Don't Know 8- Don't Know Q.53 What is the smallest number of bathrooms Q.58 What does it depend on? you can live with? 01 - One Q.59 Would you consider buying an affordable 02 - One and one-half housing unit for Kupuna only on DHHL land? 03 - Two 04 - Two and one-half 1 -Yes 05 - Three 2 - Depends 06 - Three and one-half 3 - No 07 - Four or more 8- Don't Know 08- Don't Know Q.60 What does it depend on? Hawaii Housing Planning Study, 2011: Technical Report Page 22 ©SMS, Inc. November, 2011 Q.70 Are there any other adults in your household Q.61 Would you consider buying a unit in a currently employed full-time outside the multiplex building? home for pay? 1 -Yes 1 -Yes 2 - Depends 2 - No 3 - No 9- Don't Know/Refused 8- Don't Know Q.71 What is the zip code at your work place? Q.62 What does it depend on? Q.63 Would you consider buying a home in a Q.72 How many full-time employed adults are in community or building designated for senior this household? citizens only? 1 -Yes 2 - Depends Q.73 Do you commute from home to work or 3 - No schools at least four days a week, for a 8- Don't Know distance more than a mile? 9— Refused 1 -Yes 2 - No Q.64 What does it depend on? 9- Don't Know/Refused Q.65 Would you consider buying a home in a Q.74 Do you use public transportation to get to community or building where people of all work or schools at least three times a ages live? week? 1 -Yes 1 -Yes 2 - Depends 2 - No 3 - No 9- Don't Know/Refused 8- Don't Know 9— Refused Q.75 How many other people in your household commute to work or to school at least four Q.66 What does it depend on? days a week for a distance of more than one mile? Q.67 Next, we have a few employment questions. Are you currently employed outside your home, for pay? Q.76 How many other people in your household 1 -Yes use public transportation to get to work or 2 - No schools at least three times a week? 8- Don't Know 9- Refused Q.77 Please think about the commuter in your household who travels the longest distance Q.68 What is your current employment status? to get to school or work. On average, how 1 - Full time many minutes does it take that person to 2 - Part time travel in one direction to their destination? 3 - Neither Q.78 When you move to your next home, do you Q.69 Then are you... intend on moving closer to the workplace of 1 - Unemployed and looking for work someone in the household? 2 - Retired 1 -Yes 3 - Student 2 - No 4 - Homemaker 9- Don't Know/Refused 5 - Other 9— Don't Know/Refused Q.79 Do you want to move to a place where you are closer to bus stops? 1 -Yes Hawaii Housing Planning Study, 2011: Technical Report Page 23 ©SMS, Inc. November, 2011 2 - No 9- Don't Know/Refused Q.84 One of the new kinds of housing being considered is a sustainable lease that is Q.80 Would you want to move closer to one of the used to make sure affordable homes stay in rail stations when they are built? the affordable market. 1 -Yes 2 - No Would you consider buying a leasehold 9- Don't Know/Refused property if there was a nominal monthly payment for the lease that is the lease Q.81 You're going to buy a new home. You learn payment is between $30 and $50 a month that condominium units within walking with only periodic cost of living adjustments distance of a rail station are available on for the entire lease term? (Note: Versus a Oahu. How important would that be in lease rent that is tied to the fair market your decision on where to move next? value of the land and adjusted throughout Would you say it's an... the term of the lease.) 1 - Extremely important consideration 1 -Yes 2 - Somewhat important consideration, 2 - No 3 - Not very important, or 8- Don't Know 4 - You would never consider moving to a 9— Refused condominium near a rail station 8- Not Sure Q.85 Would you consider buying leasehold if the lease term was 60 to 99 years and Q.82 You're going to rent a new home. You learn renewable? that apartments within walking distance of 1 -Yes a rail station are available on Oahu. How 2 - No important would that be in your decision on 8- Don't Know where to move next? Would you say it's 9— Refused an... 1 - Extremely important consideration Q.86 Would you consider buying leasehold if you 2 - Somewhat important consideration, could pass the home on to your heirs, and 3 - Not very important, or they started off with a new 60 to 99 year 4 - You would never consider moving to a lease? condominium near a rail station 1 -Yes 8— Not Sure 2 - No 8- Don't Know Q.83 Now, think about having a choice between 2 9— Refused new homes, both are exactly the same except for the price and location. Q.87 OK, if all that were true for all sustainable leasehold properties, that is they had a 60 For the first home you could pay the price to 99 year lease, with nominal lease you wanted and travel a shorter amount of payments, and you could pass to your heirs time you currently travel to work each day -- Do you think you would buy your next (and, thereby, reduce the amount of time home sustainable leasehold or fee simple? and cost to commute to work). 1 - Sustainable Leasehold For the second home, you could pay 2 - Fee simple $20,000 less and travel twice the time to 3 -Willing to consider sustainable leasehold work. 8- Don't Know If you had a choice, would you choose the 9- Refused home with the shorter travel time or the lower purchase price? Q.88 One way to bring down the cost of a single 1 - Shorter travel time family house is to use smaller lot sizes. If 2 - Lower priced you had a choice between a house on a 3 - Not sure smaller lot or a multifamily unit like a 9— Refused townhouse, which would you prefer? Hawaii Housing Planning Study,2011: Technical Report Page 24 0 SMS, Inc. November,2011 1 - House on a smaller lot 2 - Multifamily unit Q.94 The people in your household -- are they ALL 8- Don't Know related to you by blood, marriage or 9- Refused adoption?...OR are some who are NOT related to you at all? Q.89 Then, what would be the smallest lot size 1 - ALL are related to me you would consider? Would it be... 2 - Only SOME are related to me 1 - 3000-4000 square feet 3 - NONE are related to me 2 -4001-5000 square feet 9 - Don't Know/Refused 3 - 5001-6000 square feet 4 - Or none of the above, I need more than Q.95 Are the unrelated individuals a family 6,000 feet themselves, or are they single individuals? 8- Don't Know 1 -A family or families 9- Refused 2 - Single individuals 3 - Both Q.90 Now we have some questions for statistical 9- Don't Know/Refused purposes. What is your current marital status? Are you... Q.96 How many generations of your family live in 1 - Married your household? 2 - A member of an unmarried couple 1- One 3 - Widowed 2- Two 4 - Divorced 3- Three or more 5 - Separated 8- Don't Know/Refused 6 - Single, never married 9- Don't Know/Refused Q.97 Is there anyone living in your household, besides you, who might buy or rent in the Q.91 Including yourself, how many people live in next three years -- so you would be in two your household? different households instead of one? 01 - One 1 - Yes - someone might move out 02 - Two 2 - No 03 - Three 8- Don't Know 04 - Four 05 - Five Q.98 Do you think their next home will be in 06 - Six Hawaii or out of State? 07 - Seven 1 - In Hawaii 08 - Eight 2 - Out of State 09 - Nine 3 - Some in Hawaii, some out of State 10 - Ten or more 9- Refused 99— Don't Know/Refused Q.99 Is anybody in your household on active duty Q.92 Of the [##] people in your household, how in the military? many are. . . Under 18 years of age .._ 1 -Yes 18 to 21 .. 2 - No 22 to 34 .._ 8- Don't Know 35 to 59 .._ 60 to 74 . _ Q.100 Is anybody in your household disabled? 75 or older . 1 -Yes 2 - No Q.93 Earlier you said that you are over 60, are 8- Don't Know you... 9- Refused 1 - Under 62 Q.101 Last year at this time, where did you live? 2 - 62 or older 1 - Same house 1 year ago 9- Refused Hawaii Housing Planning Study,2011: Technical Report Page 25 0 SMS, Inc. November,2011 2 - Moved within the same county 17 - Hispanic or Latino 3 - Moved from a different county within 18 - Other same state 99- Don't Know/Refused 4 - Moved from a different state 5 - Moved from abroad Q.105 Are you 50% or more Hawaiian? 9- Refused 1 -Yes 2 - No Q.102 How long have you lived in Hawaii? 8- Not Sure, DON'T KNOW 1 - Less than 1 year 9— Refused 2 - 1 to 5 years 3 - 6 to 10 years Q.106 Are there any other people in your 4 - 11 to 20 years household are any part Hawaiian? 5 - More than 20 years, not lifetime 1 -Yes 6 - Lifetime 2 - No 8- Don't Know 8- Not Sure/Don't Know Q.103 What is your mother's ethnic background? 9- Refused 01 - Caucasian 61. 02 - Black or African-American 107 Including yourself, how many people in your 03 - Hawai'ian or Part-Hawaiian household are 50% or more Hawaiian? 04 - Japanese Q.108 What was the total 2010 income, before 05 - Chinese taxes, for all members of your household? Was it. . 06 - Filipino 07 - Korean 01 - Less than $15,000 08 - Vietnamese 02 - $15,000 to $24,999 09 - Asian Indian 03 - $25,000 to $29,999 10 - Other Asian 04 - $30,000 to $34,999 11 - Guamanian or Chamorro 05 - $35,000 to $39,999 12 - Micronesian, Chuukese, etc. 06 - $40,000 to $44,999 13 - Samoan 07 - $45,000 to $49,999 14 - Other Pacific Islander 08 - $50,000 to $59,999 15 - American Indian or Alaska Native 09 - $60,000 to $74,999 16 - Mixed, not Hawaiian 10 - $75,000 to $99,999 17 - Hispanic or Latino 11 - $100,000 to $124,999 18 - Other 12 - $125,000 to $150,000 99- Don't Know/Refused 13 - More than $150,000 Q.104 What is your father's ethnic background? 99- Don't Know/Refused 01 - Caucasian 61. 02 - Black or African-American 109 Is your annual income above or below 03 - Hawai'ian or Part-Hawai'ian 1 - Above THUD Levels] ian 04 - Japanese 1 Abe 2 - Below 05 - Chinese 06 - Filipino 9- Don't Know/Refused 07 - Korean 08 - Vietnamese Q.110 How many people in your household are 09 - Asian Indian supported on that income? 10 - Other Asian 11 - Guamanian or Chamorro Q•111 What would you do if you or your family 12 - Micronesian, Chuukese, etc. were forced to move out of your home 13 - Samoan and had no place to live? 14 - Other Pacific Islander 1 - Move in with someone else 15 - American Indian or Alaska Native 2 - Seek help from public or private agency 16 - Mixed, not Hawaiian 3 - Move to mainland Hawaii Housing Planning Study, 2011: Technical Report Page 26 ©SMS, Inc. November, 2011 4 - Move somewhere else in Hawaii 5 - Camp out on beach, in park, etc. 6 - Be homeless 7 - Just look for another place 8 - Other 88- Don't Know 99- Refused Q.112 Is anyone living in your home who is not a member of your immediate family, not paying rent, and does not have the resources to buy or rent their own place? 1 -Yes 2 - No 8- Don't Know Q.113 How many? Q.114 Thank you very much for participating in the survey. Hawaii Housing Planning Study,2011: Technical Report Page 27 0 SMS, Inc. November,2011