Longitudinal Business Database Research Articles

A Time-Lag Study of the Effect of Organisational Capital on Innovation in Australia SMEs

This study explores the strategic links between organisational capital and innovation performance in Australian SMEs. This study classified organisational capital as information technology as per hardware and software; and equipment or machinery that was applied in the firm. A sample involving SME from various industries was adapted from the Business Longitudinal Database (BLD) from the Australian Bureau of Statistics (ABS). The analyses validate that information technology capabilities is essential for achieving innovation performance. However the relationship decline over time for different type of innovation. Thus, SME managers should be carefully in investing in appropriate information technology in order to facilitate innovation in their firm.
 Key Words: SMEs, Organisational capital, Innovation, Australia

Regional differences in the effects of drought events on farm profitability in New Zealand

ABSTRACT This paper estimates the regional impact of drought, as defined by the New Zealand Drought Index (NZDI), on-farm income and profits across the main agricultural regions in New Zealand. We use farm micro-data (tax forms) from Statistics New Zealand's Longitudinal Business Database (LBD). The empirical strategy relies on region-specific panel-data models with fixed effects. We find that outcomes vary across regions and land uses. The main dairy regions (Waikato and Taranaki) have experienced significant positive impacts, likely resulting from drought-induced higher milk prices. In contrast, sheep/beef farms’ gross income and profit were negatively affected by droughts across most sheep/beef regions. Across all regions, the estimations also show that drought events do not have any observable persistent impact on farm income and profits, on average, past the first couple of years.

Government Financial Support and Firm Innovation

Prior studies have documented a positive effect of government financial support on firms’ innovation. However, such a positive effect could be due to two alternative underlying mechanisms –‘additionality’ or ‘crowding-out’. The former, whereby government financial assistance relaxes financial constraints for recipient firms and enables their innovation, represents the desired positive effect. On the other hand, the crowding-out mechanism – whereby financially unconstrained recipient firms use government funding to simply replace their private spending – represents mistargeted government intervention. This paper attempts to disentangle these two mechanisms to understand which one of them drives empirical observations of a positive effect of government funding on firm innovation. We achieve this through formulating and testing two competing moderator hypotheses, each one being a unique derivative of the additionality and crowding-out mechanisms respectively. Our empirical analysis uses firm-level panel data from the Business Longitudinal Database (BLD) compiled by the Australian Bureau of Statistics (ABS), 2011-2016, and addresses both endogeneity and selection problems in our estimation. We find that government financial support increases the number of innovation that recipient firms produce. However, we also find that this positive effect is likely a result of the crowding-out mechanism. Financially unconstrained firms appear to benefit more from government support than financially constrained firms.

Building on Aotearoa New Zealand’s Integrated Data Infrastructure

Stats NZ established the Integrated Data Infrastructure (IDI) to enable longitudinal research into the causes and correlates of social outcomes for New Zealanders. The IDI was established in 2011, building off earlier experiences linking employer and employee data (which itself subsequently formed the basis of another linked database known as the Longitudinal Business Database [LBD]). Data in the IDI form an ‘ever-resident’ Aotearoa New Zealand population of around nine million people. Access to the IDI is available for bona fide researchers so long as they meet established criteria to show that they will keep the data safe and work with it in a culturally appropriate way. This article gives a brief history to the development of the IDI (and the LBD) and shares some lessons learned along the way for the benefit of others starting down this integrated data journey.

Profit Pools and Determinants of Potential County-Level Manufacturing Growth

Business location research often focuses on evaluating specific policies or explaining outcomes for a particular region. Further, the micro-foundations of random profit maximization supporting manufacturing location analysis often lack the intuitive nature of demand thresholds. While this article maintains these micro-foundations, it introduces a unifying concept of profit pools and examines how proximate supply/cost factors determine potential local manufacturing size. The approach avoids a number of limitations associated with other locational choice models. Restricted-access establishment-level data from the Longitudinal Business Database along with secondary data sources produce a model to estimate county-level contributors to outcomes of manufacturing establishment growth and consolidation. The analysis offers improved methods and accuracy for modeling establishment location outcomes, including accuracy in measuring industry size and methods for choosing among various count data distributions. The locational factors associated with county-level potential for manufacturing vary in magnitude and significance depending on the type of manufacturing, while affirming the importance of agglomeration across manufacturing types.

Of interest? Estimating the average interest rate on debt across firms and over time

We use tax data from the Longitudinal Business Database to estimate the firm-level average interest rate on liabilities. The mean of this measure has similar time series properties to official statistics on the business borrowing rate, while also enabling detailed disaggregation across different firm types. We document significant variation in interest rate across firms in different industries, and across firms with different apparent borrowing risk. Finally, we compare firms self-reported views on whether they are finance-constrained to an estimated firm-specific interest rate premium, showing that: finance-constrained firms have higher interest rate premia than unconstrained firms; and that at least part of this difference in premia is explained by firm level differences in risk between constrained and unconstrained firms.

Freight mode choice: Results from a nationwide qualitative and quantitative research effort

Abstract The research reported in this paper focused on studying various aspects of freight mode choice in the continental United States (US) including the influencing factors, the development of econometric models to assess the impacts of public-sector policies and changes in market conditions. To gain insight into this complex subject, the team used qualitative and quantitative research techniques. The qualitative effort involved In-Depth Interviews (IDIs) with a highly selective group of leading shippers, carriers, and receivers. The IDIs provided insight into the key factors that influence mode choice, and the barriers that limit mode shifts. The quantitative effort estimated econometric models that express freight mode choice as a function of key independent variables. A unique aspect of this research is that the models were estimated using high-quality confidential data under the custody of the United States’ Census Bureau, the Internal Revenue Service, and the Surface Transportation Board, including: the Commodity Flow Survey (CFS), the largest shipper survey in the world; the Longitudinal Business Database (LBD), a comprehensive registry of commercial establishments in the US; and the Waybill Sample, a 5% sample; together with custom-made datasets of modal characteristics prepared by the authors. Using these data, the team estimated discrete-continuous freight mode choice models representing the choice of rail or truck for 42 different commodity types, and different combinations of independent variables and weighting schemes. The paper concludes with a discussion of the policy implications of the research conducted.

Access to Linked Administrative Data Through an Indigenous Cultural Lens

IntroductionStats NZ provides the world-leading Integrated Data Infrastructure (IDI) to help improve New Zealanders’ lives. Ngā Tikanga Paihere (the Tikanga Framework) is a tool designed to ensure data use is carefully considered, and practice occurs in good faith. It also aims to build and maintain public trust and confidence in the way Stats NZ manages administrative data in the IDI. It draws on general customary concepts from Te Ao Māori (Māori world) and sits in alignment with the current model of the Five Safes Framework for access. Objectives and ApproachTikanga are appropriate customary practices or ‘layers of the culture’ developed by Māori communities and individuals and informed by common cultural values and concepts. Stats NZ applies the framework when reviewing applications to use data in the IDI and Longitudinal Business Database (LBD). The framework is used with the original ‘Five Safes’ framework in the review process to ensure that data will be used in an appropriate and collaborative way, without marginalising any specific populations. In research proposals relating specifically to Māori, researchers are asked to demonstrate what value their work will bring to Māori communities and how the researchers will work collaboratively with those communities. ResultsUse of Ngā Tikanga Paihere has been well received. Stats NZ is now looking to broaden the use of Ngā Tikanga Paihere to assess all integrated data research proposals that focus on minority, identifiable, and marginalised populations. Conclusion / ImplicationsWhile Ngā Tikanga Paihere does not resolve data governance or cultural licence issues, it encourages researchers to actively engage and collaborate with Māori groups when these communities are potentially impacted, or when the project might use data about these communities. Stats NZ sees data governance and cultural licence matters as an ongoing conversation between agencies and Treaty/Te Tiriti partners. Ngā Tikanga Paihere should be a tool to help guide the government data system to work with Māori data ‘in good faith’.

An overview of Integrated Data at Stats NZ

IntroductionStats NZ works with a range of organisations to provide the world-leading Integrated Data Infrastructure (IDI) to help improve New Zealanders’ lives. Stats NZ’s integrated data is a critical tool in the New Zealand government’s efforts to reduce poverty, improve health, and provide a growing, inclusive economy. It enables researchers to gain evidence-based insights, and to measure the effectiveness of government initiatives and services. Objectives and ApproachThe IDI contains de-identified longitudinal unit record data about people and households. Access is provided when projects meet the ‘five safes’ framework, which ensures the data is kept safe. As well as this, the project must meet the standards of Ngā Tikanga Paihere, a customs-based framework that applies a Te Ao Māori lens to managing IDI access. We also produce the Longitudinal Business Database (LBD) which contains de-identified longitudinal microdata about businesses. ResultsThe IDI has proved to be a vital tool to assist with decision making and insights on topical areas. There are currently approximately 550 researchers using the IDI for 280 different research projects. These researchers are from government agencies, universities and non-government organisations studying issues like vulnerable children, education and employment outcomes, impact of health conditions, business productivity and more. Conclusion / ImplicationsThe number of projects and users continues to increase, with a large increase to the number of users projected for 2020/2021. The way our customers use data has changed since the establishment of the IDI, and the broader demand for data-driven evidence has with it. We are making changes to ensure that we can cope with increasing demand and ensure that those that need to access our services can.

A Growing Problem: Exploring Livestock Farm Resilience to Droughts in Unit Record Data.

Climate models indicate that New Zealand’s farms will be increasingly exposed to adverse climate events in the future. In this study, we empirically investigate drought impacts on farm enterprises by linking financial, agricultural and productivity data from Statistics New Zealand’s Longitudinal Business Database (LBD) with historical weather data from NIWA. Our sample consists of an unbalanced panel of over 67,000 observations of livestock farm enterprises between 2002 and 2012. We run a set of panel regressions with time and farm fixed effects to estimate the effect of changes in drought intensity on gross output, profit per hectare, current loans and intermediate expenditure of dairy and sheep-beef farms. To explore factors of resilience to droughts, we also examine how the estimates change with different farm characteristics. Most (but not all) of the estimated drought effects are significant, consistent across various specifications and of the expected sign. However, we have limited success in conclusively identifying farm characteristics that affect drought outcomes in our data.

How Destructive is Innovation?

Entrants and incumbents can create new products and displace the products of competitors. Incumbents can also improve their existing products. How much of aggregate productivity growth occurs through each of these channels? Using data from the U.S. Longitudinal Business Database on all non-farm private businesses from 1976–1986 and 2003–2013, we arrive at three main conclusions: First, most growth appears to come from incumbents. We infer this from the modest employment share of entering firms (defined as those less than 5 years old). Second, most growth seems to occur through improvements of existing varieties rather than creation of brand new varieties. Third, own-product improvements by incumbents appear to be more important than creative destruction. We infer this because the distribution of job creation and destruction has thinner tails than implied by a model with a dominant role for creative destruction.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Measuring Job Creation, Growth, and Survival among the Universe of Start-ups in the United States Using a Combined Start-up Panel Data Set

The field of entrepreneurship is growing rapidly and expanding into new areas. This article presents a new compilation of administrative panel data on the universe of business start-ups in the United States, which will be useful for future research in entrepreneurship. To create the US start-up panel data set, the authors link the universe of non-employer firms to the universe of employer firms in the Longitudinal Business Database (LBD). Start-up cohorts of more than five million new businesses per year, which create roughly three million jobs, can be tracked over time. To illustrate the potential of the new start-up panel data set for future research, the authors provide descriptive statistics for a few examples of research topics using a representative start-up cohort.

A portrait of U.S. firms that invest in R&D

ABSTRACTThis paper combines micro-level cross-sectional data from the Survey of Industrial Research and Development (SIRD) and the Business Research & Development and Innovation Survey (BRDIS) with the Longitudinal Business Database (LBD) to characterize U.S. firms that invest in research and development (R&D). The result is a firm-level panel data set from 1992 to 2013 that tracks firms as they enter and exit the R&D surveys. Using R&D expenditures to proxy R&D performance, we find that the majority of R&D is performed by large manufacturing firms that export, but the composition of R&D performing firms has gradually shifted more towards smaller nonmanufacturing firms. We find a high degree of persistence in R&D investment with previous R&D experience being a significant determinant of current R&D intensity, even after controlling for individual firm effects. We also uncover differences in observable firm characteristics between manufacturing and nonmanufacturing, as well as small and large, R&D performing firms.

Improved Productivity Measurement in New Zealand's Longitudinal Business Database

Accounts information that businesses supply to Inland Revenue for tax purposes provide over 96% of the observations in the productivity dataset in the Longitudinal Business Database. In 2013, material changes in the data collected halted the annual updating of the productivity dataset. This paper describes a method for accounting for these raw data discontinuities, and revisits the prior productivity dataset methodology, implementing wholesale changes that improve the overall quality of the data and the versatility of the productivity dataset.

How Destructive Is Innovation?

Entrants and incumbents can create new products and displace the products of competitors. Incumbents can also improve their existing products. How much of aggregate productivity growth occurs through each of these channels? Using data from the U.S. Longitudinal Business Database on all nonfarm private businesses from 1983 to 2013, we arrive at three main conclusions: First, most growth appears to come from incumbents. We infer this from the modest employment share of entering firms (defined as those less than 5 years old). Second, most growth seems to occur through improvements of existing varieties rather than creation of brand new varieties. Third, own‐product improvements by incumbents appear to be more important than creative destruction. We infer this because the distribution of job creation and destruction has thinner tails than implied by a model with a dominant role for creative destruction.

Leverage over the Firm Life Cycle, Firm Growth, and Aggregate Fluctuations

We study the leverage of U.S. firms over their life cycles and the connection between firm leverage, firm growth, and aggregate shocks. We construct a new dataset that combines private and public firms' balance sheets with firm-level data from U.S. Census Bureau's Longitudinal Business Database for the period 2005-12. Public and private firms exhibit different leverage dynamics over their life cycles. Firm age and size are systematically related to leverage for private firms but not for public firms. We show that private firms, but not public ones, deleveraged during the Great Recession and that this deleveraging is associated with a reduction in firm revenue and employment growth. Exploiting sectoral variation, we find that the leverage dynamics of firms is also relevant for aggregate fluctuations.

The Longitudinal Impact of Intellectual Capital on Innovation Performance in SMEs

In the 1980’s, many economists emphasize on the importance of innovation in promoting the country’s economic growth. The issue of innovation performance has received considerable critical attention among SMEs. Scholars have long debated the impact of Research and Development (R&D) on the creation and diffusion of innovation in companies. The key drivers of firms’ innovation should be explored beyond R&D. To date, most public policy still relies on the assumption of the number of patents and the amount of investment made on R&D. Recently, a significant literature on the theme of intangible assets such as skills, knowledge management and intellectual capital has been developed around innovation performance. In fact, several researchers proposed that intellectual capital can benefit innovation performance in several ways. This study investigated from various industries of SMEs in Australia using data from the Business Longitudinal Database (BLD) from the Australian Bureau of Statistics (ABS). The findings concluded that the relational capital and structural capital links with innovation performance are significant after two years-lagged. SC is the most significant predictor of innovation performance while human capital does not significant related to innovation performance in SMEs. Nevertheless, in the long term, SC plays an important role in organisational innovation.  The enduring outcomes of this study emphasize several possibilities which would help SME managers and policy makers to better foster innovation performance.

On the U.S. Firm and Establishment Size Distributions

This paper revisits the empirical evidence on the nature of firm and establishment size distributions in the United States using the Longitudinal Business Database (LBD), a confidential Census Bureau panel of all non-farm private firms and establishments with at least one employee. We establish five stylized facts that are relevant for the extent of granularity and the nature of growth in the U.S. economy: (1) with an estimated shape parameter significantly below 1, the best-fitting Pareto distribution substantially differs from Zipf's law for both firms and establishments; (2) a lognormal distribution fits both establishment and firm size distributions better than the commonly-used Pareto distribution, even far in the upper tail; (3) a convolution of lognormal and Pareto distributions fits both size distributions better than lognormal alone while also providing a better fit for the employment share distribution; (4) the estimated parameters are different across manufa cturing and services sectors, but the distribution fit ranking remains unchanged in the sectoral subsamples. Finally, using the Census of Manufactures (CM), we find that (5) the distribution of establishment-level total factor productivity---a common theoretical primitive for size---is also better described by lognormal than Pareto. We show that correctly characterizing the firm size distribution has first order implications for the effect of firm-level idiosyncratic shocks on aggregate activity.

What's driving innovation in small businesses in Australia? The case of the food industry

There is strong evidence that innovation is a primary driver of a nation's economic growth. As Australia continues to compete in the global economy, it is imperative that businesses should be innovative to improve their performance. In this paper, we evaluate the status and main drivers of innovation in small businesses in the food sector in Australia. Discrete choice modelling and bootstrapping procedures are applied to a panel of firm‐level data collected through theABSBusiness Characteristics Survey (2006–2007 to 2010–2011 for the Australian Bureau of Statistics’ Business Longitudinal Database Confidential Unit Record File) to investigate the factors affecting the likelihood of small food businesses to innovate. Results show that businesses are more likely to innovate if they collaborate, have higher information and communication technology intensity, and use science, technology, engineering and mathematics skills. We also found that small food businesses, even at the subsector level, do combine different types of innovation when innovating. The propensity to innovate also increases for small businesses that have flexible working arrangements, face moderate‐to‐strong market competition, operate overseas and seek finance through debt and equity. The relative importance of these factors was found to vary between agricultural and nonagricultural food subsectors.

When Liability Becomes Potential: Intermediary Entrepreneurship in Dynamic Market Contexts

This paper analyzes how entrepreneurs fare in an intermediary market segment when the segment is closely attached to a single supplier market. While focusing on two structural constraints, organizational structure and competitive pressure, I build off of the fact that in the past thirty years in the U.S. beer industry, as the number of beer producers (i.e. brewers) proliferated, their intermediaries (i.e. wholesalers) declined. Using establishment-level restricted-access economic microdata from the Longitudinal Business Database, I examine what happens with intermediaries when (some) producers start competing on product variety instead of competing on scale. Piecewise exponential survival models show that Stinchcombe’s ‘liability of newness’ principle can get suspended and certain newcomers have better survival chances than industry incumbents. I call this effect the potential of newness under which entrepreneurial establishments fare better if they are part of well-resourced multiunit firms. Furthermore, I show that these resource-rich entrepreneurs benefit from the potential of newness especially in areas with competition-laden history and where the industry experiences shakeouts. For market incumbents, the more competition-laden the history of the local market, the higher the hazards of current time establishment failure. For multiunit entrepreneurs, however, a more competition-laden history of the local market is associated with a decrease in the hazards of current time establishment failure. This paper highlights that market structure not only enables but sometimes traps already existing organizations and make them less adaptive to changing logics of competition. The results highlight how organizational factors and geography create inequalities among intermediary organizations.