Longitudinal Business Database Research Articles

The Influence of Intellectual Capital on Product, Process and Administration Innovation in the SMEs Context.

There are insufficient studies that investigate the connection between human, structural and relational capital and organizational innovation in Australian SMEs in the literature. Various SMEs industries, in Australia were adapted from Business Longitudinal Database (BLD) from the Australian Bureau of Statistics (ABS). This cross-sectional study shows that relational and human capitals are positive and significant towards process innovation while relational capital is the only predictor for product innovation. The results also show that human, structural and relational capitals were the most significant predictor for administration innovation. The findings show that relational capital has the most significant relationship between the three components of intellectual capital towards innovation in Australia SMEs. SME managers acknowledged the importance in collaboration towards achieving innovation performance in their firm. In order for SMEs to be a competitive advantage, managers should focus to improve their networking and collaboration with external parties, so that the whole innovation (product, process and administration innovation) can be achieve.

Moving on from New Zealand’s productivity paradox

For many years New Zealand’s productivity performance has been disappointing. The authors outline recent progress in understanding what could be driving this performance. They draw on Statistics New Zealand industry-level data, before summarising insights from firm-level research using linked data sets (the Longitudinal Business Database (LBD)). They conclude with a high-level summary of directions of reform that could help improve New Zealand’s productivity performance.

Private Equity, Jobs, and Productivity: Reply to Ayash and Rastad

Ayash and Rastad (2017) express several concerns about our 2014 analysis of private equity buyouts. We welcome their interest in our work but think their criticisms are off the mark. Some of their claims reflect a misunderstanding of the Census Bureau’s Longitudinal Business Database (LBD) and its underlying data inputs. Because the LBD has emerged as a major laboratory for empirical studies in economics and finance, we use this opportunity to reiterate and clarify some of its important features. In a similar spirit, we elaborate on steps taken to develop our large sample of private equity buyouts. We also address Ayash and Rastad’s remarks about the empirical design of our establishment-level analysis, our methods for distinguishing between leveraged buyouts (LBOs) and other private equity transactions, bankruptcy rates among firms acquired in LBOs, their assertion that we undercount large public-to-private LBOs, and other matters.

The impact of government financial assistance on the performance and financing of Australian SMEs

PurposeThis paper aims to examine the impact of government financial assistance provided to Australian small and medium-sized enterprises (SMEs).Design/methodology/approachThis study uses firm-level panel data on more than 2,000 SMEs over a five-year period from the Business Longitudinal Database compiled by the Australian Bureau of Statistics. The authors measure the impact of government financial assistance in terms of subsequent SME performance (income from sales of goods and services and profitability) and changes in the availability of alternative nongovernment finance.FindingsThe authors find government financial assistance helps SMEs improve performance over and above the effects of conventional financing. They also find than the implicit guarantee effect signalled by a firm receiving government financial assistance suggests firms are more likely to obtain nongovernment finance in the future. Control factors that significantly affect SME performance and finance availability include business size, the level of innovation, business objectives and industry.Research limitations/implicationsNearly all of the responses in the original survey data are qualitative, so we are unable to assess how the strength of these relationships varies by the levels of assistance, income and profitability. The measure of government financial assistance of the authors is also general in that it includes grants, subsidies and rebates from any Australian Government organisation, so we are unable to comment on the impact of individual federal, state or local government programmes.Practical implicationsGovernment financial assistance helps SMEs improve both immediate and future performance as measured by income and profitability. This could be because government financial assistance quickly overcomes the financial constraints endemic in SMEs. Government financial assistance also helps SMEs obtain nongovernment finance in the future. The authors conjecture that this is because it overcomes some of the information opaqueness of SMEs.Originality/valueFew studies focus on the impact of direct government financial assistance compared with indirect assistance as typical in credit guarantee schemes. The authors use a very large and detailed data set on Australian SMEs to undertake the analysis.

Gun Shops as Local Institutions: Federal Firearms Licensees, Social Disorganization, and Neighborhood Violent Crime

Recently, scholars have argued that local social and economic institutions, such as bars and payday lenders, can influence neighborhood crime outcomes. Drawing on routine activities theory and social disorganization theory, such research has posited that such institutions can directly affect crime rates by providing potential targets or encouraging criminal behavior, and can indirectly affect crime rates by discouraging social control efforts. We draw on this literature, as well as the literature on reactions to firearm prevalence, to examine the effects of gun shops on local crime rates. Using data for the year 2000 drawn from the National Neighborhood Crime Study (NNCS), the Bureau of Alcohol, Tobacco, Firearms, and Explosives' Federal Firearms Licensees Database (FFLD), and the National Establishment Time-Series Longitudinal Business Database (NETS), we use hierarchical linear models to examine how the prevalence of gun shops at the tract and metro level contribute to tract-level rates of violent crime in eighty-nine large US cities. Our findings indicate that gun shop prevalence in urban areas is associated with increased rates of homicides and robberies, and that these effects are more pronounced in neighborhoods characterized by residential instability. We conclude with a discussion of policy considerations and avenues for future research on local institutions.

Flexible working arrangements and strategic positions in SMEs

PurposeUnder the Australian Fair Work Act 2009, employees can request flexible working arrangements (FWAs) from their employers. Provision of FWAs is costly to small and medium enterprises (SMEs). They can, however, use FWAs to achieve competitive advantage. The purpose of this paper is to investigate strategic positions associated with FWA availability in SMEs. It also examines the effects of size and industry sector on FWA availability in SMEs.Design/methodology/approachWith a sample of 1,541 cases comprising micro, small and medium firms from the Australian Bureau of Statistics’ Business Longitudinal Database, binary regression models were used to analyse the relationships between FWAs and the independent variables: strategic position, firm-size and industry of operation.FindingsFlexible working hours, flexible leave arrangements and roster/shift selection were used by SMEs pursuing a strategy focussed on human resources. In contrast, a strategic focus on cost correlated negatively with paid parental leave and flexible rosters/shifts. SMEs pursuing innovation were unlikely to provide flexible leave while job sharing was less visible in SMEs focussing on quality. An industry effect was evident with working from home unlikely for firms in industry sectors where employees had to be present at work. Micro- and small-sized firms were less likely than medium firms to provide FWA to their employees.Originality/valueSMEs with competitive positions based on human capital could use FWAs to attract the required skills. Employees in SMEs that compete on cost may benefit from FWAs in the form of temporary and casual positions.

Firms' Internal Networks and Local Economic Shocks

This paper shows that firms spread the adverse impacts of local employment shocks across regions through their internal networks of establishments. Linking confidential micro data at the establishment level from the U.S. Census Bureau’s Longitudinal Business Database to ZIP code-level variation in house price changes during the Great Recession, we find that local establishment-level employment responds strongly to employment shocks in other regions in which the firm has establishments. Consistent with theory, the elasticity of establishment-level employment with respect to shocks in other regions is increasing with firms’ financial constraints. Moreover, establishments belonging to more expansive firm networks exhibit smaller employment elasticities with respect to their own local shocks. To account for the impacts of general equilibrium adjustments, we examine aggregate employment at the county level. Similar to what we found at the establishment level, we obtain large elasticities of county-level employment with respect to employment shocks in other counties linked through firms’ internal networks. Overall, our results suggest that firms play an important role in the provision of regional risk sharing and the propagation of local employment shocks across different U.S. regions.

Firms’ Internal Networks and Local Economic Shocks

Using confidential establishment-level data from the US Census Bureau’s Longitudinal Business Database, this paper documents how local shocks propagate across US regions through firms’ internal networks of establishments. Consistent with a model of optimal within-firm resource allocation, we find that establishment-level employment is sensitive to shocks in distant regions in which the establishment’s parent firm is operating, and that the elasticity with respect to such shocks increases with the firm’s financial constraint. At the aggregate regional level, we find that aggregate county-level employment is sensitive to shocks in distant counties linked through firms’ internal networks. (JEL D22, G32, L14, L22, R23, R32)

Simultaneous edit-imputation and disclosure limitation for business establishment data

ABSTRACTBusiness establishment microdata typically are required to satisfy agency-specified edit rules, such as balance equations and linear inequalities. Inevitably some establishments' reported data violate the edit rules. Statistical agencies correct faulty values using a process known as edit-imputation. Business establishment data also must be heavily redacted before being shared with the public; indeed, confidentiality concerns lead many agencies not to share establishment microdata as unrestricted access files. When microdata must be heavily redacted, one approach is to create synthetic data, as done in the U.S. Longitudinal Business Database and the German IAB Establishment Panel. This article presents the first implementation of a fully integrated approach to edit-imputation and data synthesis. We illustrate the approach on data from the U.S. Census of Manufactures and present a variety of evaluations of the utility of the synthetic data. The paper also presents assessments of disclosure risks for several intruder attacks. We find that the synthetic data preserve important distributional features from the post-editing confidential microdata, and have low risks for the various attacks.

High Growth Young Firms: Contribution to Job, Output and Productivity Growth

Recent research shows that the job creating prowess of small firms in the U.S. is better attributed to startups and young firms that are small. But most startups and young firms either fail or don’t create jobs. A small proportion of young firms grow rapidly and they account for the long lasting contribution of startups to job growth. High growth firms are not well understood in terms of either theory or evidence. Although the evidence of their role in job creation is mounting, little is known about their life cycle dynamics, or their contribution to other key outcomes such as real output growth and productivity. In this paper, we enhance the Longitudinal Business Database with gross output (real revenue) measures. We find that the patterns for high output growth firms largely mimic those for high employment growth firms. High growth output firms are disproportionately young and make disproportionate contributions to output and productivity growth. The share of activity accounted for by high growth output and employment firms varies substantially across industries – in the post 2000 period the share of activity accounted for by high growth firms is significantly higher in the High Tech and Energy related industries. A firm in a small business intensive industry is less likely to be a high output growth firm but small business intensive industries don’t have significantly smaller shares of either employment or output activity accounted for by high growth firms.

Spatial Organization of Firms and Location Choices Through the Value Chain

We explore the impact of geographically bounded, intrafirm linkages (internal agglomerations) and geographically bounded, interfirm linkages (external agglomerations) on firms’ location strategies. Using data from the Census Bureau’s Longitudinal Business Database, we analyze the locations of new establishments of biopharmaceutical firms in the United States from 1993 to 2005. We consider all activities in the value chain and allow location choices to vary by research and development, manufacturing, and sales. Our findings suggest that internal agglomerations have a positive impact on location. The effects of internal agglomerations vary by activity, and they arise both within an activity (e.g., among plants) and across activities (e.g., between sales and manufacturing). Our results also suggest that previous estimates of the effect of external agglomerations may be overestimated because the existing literature abstracted from internal agglomerations. This paper was accepted by Bruno Cassiman, business strategy.

Redistribution of Local Labor Market Shocks through Firms' Internal Networks

Local labor market shocks are difficult to insure against. Using confidential micro data from the U.S. Census Bureau’s Longitudinal Business Database, we document that firms redistribute the employment impacts of local demand shocks across regions through their internal networks of establishments. During the Great Recession, the massive decline in house prices caused a sharp drop in consumer demand, leading to large employment losses in the non-tradable sector. Consistent with firms smoothing out the impacts of these shocks across regions, we find large elasticities of non-tradable establishment-level employment with respect to house prices in other counties in which the firm has establishments. At the same time, establishments of firms with larger regional networks exhibit lower employment elasticities with respect to local house prices in the establishment’s own county. To account for general equilibrium adjustments, we aggregate non-tradable employment at the county level. Similar to what we found at the establishment level, we find that non-tradable county-level employment responds strongly to local demand shocks in other counties linked through firms’ internal networks. These results are not driven by direct demand spillovers from nearby counties, common shocks to house prices, or local demand shocks affecting non-tradable employment in distant counties indirectly via the trade channel. Our results suggest that firms play an important role in the extent to which local labor market risks are shared across regions.

Employment Dynamics of Australian Entrepreneurship: A Management Perspective

This article attempts to draw together the literature on high-growth firms and management capability using Australian Government data from the Expanded Analytical Business Longitudinal Database. We tracked cohorts of new micro-sized firms (startups) over five years from birth. Compared with startups that had a low employment growth trajectory, mediumand high-growth micro-startups exhibited higher financial performance, higher innovation activity, and a greater propensity to seek external (debt or equity) finance. From a management perspective, medium- and high-growth startups were also significantly more likely to monitor and assess their performance across a wider range of performance indicators. High-growth micro-startups exhibited significantly higher operational process and organizational/managerial innovation, a higher likelihood of foreign ownership, and a greater demand for equity finance than medium-growth micro-startups. This data is consistent with other evidence that suggests that sustained high growth comes from superior strategic management and may suggest an ongoing role for government policy in building firm management capability in order to foster employment growth. Entrepreneurs – the most successful, though not the only, practitioners of innovation – rarely stop to examine how they do it. Most of them simply get on with the job of creating value by exploiting some form of change – be it in technology, materials, prices, taxation, demographics, or even geopolitics.

Taxation, corruption, and growth

We build an endogenous growth model to analyze the relationships between taxation, corruption, and economic growth. Entrepreneurs lie at the center of the model and face disincentive effects from taxation but acquire positive benefits from public infrastructure. Political corruption governs the efficiency with which tax revenues are translated into infrastructure. The model predicts an inverted-U relationship between taxation and growth, with corruption reducing the optimal taxation level. We find evidence consistent with these predictions and the entrepreneurial channel using data from the Longitudinal Business Database of the US Census Bureau. The marginal effect of taxation for growth for a state at the 10th or 25th percentile of corruption is significantly positive; on the other hand, the marginal effects of taxation for growth for a state at the 90th percentile of corruption are much lower across the board. We make progress towards causality through Granger-style tests and by considering periphery counties where effective tax policy is largely driven by bordering states. Finally, we calibrate our model and find that the calibrated taxation rate of 37% is fairly close to the model׳s estimated welfare maximizing taxation rate of 42%. Reducing corruption provides the largest potential impact for welfare gain through its impact on the uses of tax revenues.

Taking the Leap: The Determinants of Entrepreneurs Hiring Their First Employee

Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of start‐ups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a nonemployer to employer firm among start‐ups. Several interesting patterns emerge regarding the dynamics of nonemployer start‐ups hiring their first employee. Hiring rates among the universe of nonemployer start‐ups are very low, but increase when the population of nonemployers is focused on more growth‐oriented businesses such as incorporated and employer identification number businesses. If nonemployer start‐ups hire, the bulk of hiring occurs in the first few years of existence. After this point in time, relatively few nonemployer start‐ups hire an employee. Focusing on more growth‐ and employment‐oriented start‐ups in the KFS, we find that Asian‐owned and Hispanic‐owned start‐ups have higher rates of hiring their first employee than white‐owned start‐ups. Female‐owned start‐ups are roughly 10 percentage points less likely to hire their first employee by the first, second, and seventh years after start‐up. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that nonemployers hire their first employee.

Taking the Leap: The Determinants of Entrepreneurs Hiring Their First Employee

Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of startups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a non-employer to employer firm among startups. Several interesting patterns emerge regarding the dynamics of non-employer startups hiring their first employee. Hiring rates among the universe of non-employer startups are very low, but increase when the population of non-employers is focused on more growth-oriented businesses such as incorporated and EIN businesses. If non-employer startups hire, the bulk of hiring occurs in the first few years of existence. After this point in time relatively few non-employer startups hire an employee. Focusing on more growth- and employment-oriented startups in the KFS, we find that Asian-owned and Hispanic-owned startups have higher rates of hiring their first employee than white-owned startups. Female-owned startups are roughly 10 percentage points less likely to hire their first employee by the first, second and seventh years after startup. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that non-employers hire their first employee.

Using partially synthetic microdata to protect sensitive cells in business statistics

We describe and analyze a method that blends records from both observed and synthetic microdata into public-use tabulations on establishment statistics. The resulting tables use synthetic data only in potentially sensitive cells. We describe different algorithms, and present preliminary results when applied to the Census Bureau's Business Dynamics Statistics and Synthetic Longitudinal Business Database, highlighting accuracy and protection afforded by the method when compared to existing public-use tabulations (with suppressions).

Using Partially Synthetic Microdata to Protect Sensitive Cells in Business Statistics

We describe and analyze a method that blends records from both observed and synthetic microdata into public-use tabulations on establishment statistics. The resulting tables use synthetic data only in potentially sensitive cells. We describe different algorithms, and present preliminary results when applied to the Census Bureau's Business Dynamics Statistics and Synthetic Longitudinal Business Database, highlighting accuracy and protection afforded by the method when compared to existing public-use tabulations (with suppressions).

Taking the Leap: The Determinants of Entrepreneurs Hiring Their First Employee

Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of startups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a non-employer to employer firm among startups. Several interesting patterns emerge regarding the dynamics of non-employer startups hiring their first employee. Hiring rates among the universe of non-employer startups are very low, but increase when the population of non-employers is focused on more growth-oriented businesses such as incorporated and EIN businesses. If non-employer startups hire, the bulk of hiring occurs in the first few years of existence. After this point in time relatively few non-employer startups hire an employee. Focusing on more growth- and employment-oriented startups in the KFS, we find that Asian-owned and Hispanic-owned startups have higher rates of hiring their first employee than white-owned startups. Female-owned startups are roughly 10 percentage points less likely to hire their first employee by the first, second and seventh years after startup. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that non-employers hire their first employee.

Firm Productivity Growth and Skill

This paper examines the relationship between firm multifactor productivity growth (mfp) and changing skill levels of labour in New Zealand, over the period 2001-12, using longitudinal data from Statistics New Zealand's Longitudinal Business Database (LBD) and Integrated Data Infrastructure (IDI). We estimate that the average skill of workers declined by 1.8% over the period, reflecting strong employment growth for workers with lower than average skill levels. The net decline was the combined effect of a 3.6% decline in unobserved skill outweighing a 1.8% increase in observed skill, resulting in 1.8% slower estimated skill-adjusted labour growth (13.3%) than the 15.0% growth in full-time equivalent (FTE) employment. Mirroring the skill-dilution, skill-adjusted mfp growth averaged 0.24% per annum over the period compared to 0.14% pa for unadjusted growth. The patterns were stronger over the pre-GFC period to 2008, during which adjusted and unadjusted mfp grew 0.57% pa and 0.42% pa respectively. Our analysis of the effect of changing skill on mfp growth finds that the impact of skill adjustment was almost entirely due to changing skill composition within continuing firms.