resilience_relatedness_tr.csv

This study utilizes multiple datasets spanning the period 2008–2022 to analyze regional economic resilience at the NUTS-3 level in Turkey, focusing on the effects of related and unrelated variety. Data sources include the Statistical Yearbooks of the Social Security Institution (SSI) and the Turkish Statistical Institute (TURKSTAT). Employment data were sourced from the SSI and include information on insured employees under 4-a, classified according to the NACE Rev. 2 sectoral classification. Employees within the scope of 4-a primarily represent private-sector workers, as public sector employees with job guarantees are excluded from this category. This distinction is critical because public sector employees are largely insulated from economic shocks, whereas private-sector employment more accurately reflects the labor market's vulnerability and response to shocks. This data allows us to calculate employment-based resilience metrics, following the methodology of Martin et al. (2016). However, recognizing the significant informal employment problem in Turkey, as highlighted by Eraydın (2016), GDP data were also incorporated as a complementary measure of economic resilience. GDP data at the provincial level, also classified by NACE Rev. 2, were obtained from TURKSTAT and used alongside employment data to provide a comprehensive picture of regional resilience. In addition to GDP and employment data, provincial export data were utilized to calculate related and unrelated variety at the provincial level in Turkey. These data, categorized under the SITC Rev. 3 classification, were sourced from TURKSTAT. To ensure the robustness of the analysis and to isolate the effects of related and unrelated variety, several control variables were incorporated into the study. These include the proportion of employees without social security (SocS), exports to the European Union (ExEU), and a dummy variable (CrossB) that accounts for development differences between the eastern and western regions of Turkey.The proportion of employees without social security (SocS) serves as a proxy for the prevalence of informal employment, a defining feature of the Turkish labor market. Informality can amplify economic vulnerabilities due to limited access to social protection mechanisms and the lower productivity of informal firms. However, it may also provide flexibility and act as a buffer during downturns by creating employment opportunities when the formal sector contracts. Exports to the EU (ExEU), Turkey’s largest trading partner, were included due to their significant role in the country’s economic performance. The EU’s relatively stable demand contribute to economic resilience by providing predictable export revenues. However, Turkey’s dependence on the EU also creates vulnerabilities, particularly during periods of economic instability. Finally, a dummy variable (CrossB) was created to reflect the development differences between the east and west of Turkey, which manifest themselves in various economic and social dimensions. This variable specifically identifies the 13 provinces in the east and southeast of Turkey covered by cross-border trade with neighboring countries, assigning a value of 1 to these provinces and 0 to the remaining 68 provinces. Cross-border trade in these 13 provinces serves as an additional opportunity for these provinces to increase their export volumes, thereby contributing to improved well-being and income levels in these regions. When calculating related and unrelated variety based on export data, this differentiation is particularly relevant for understanding regional variations in economic structure and resilience. To further explore these dynamics, the model also includes interaction terms between this dummy variable (CrossB) and the related and unrelated variety indices.<br>

本研究采用2008—2022年的多套数据集，对土耳其NUTS-3级别的区域经济韧性展开分析，重点关注相关多样化与非相关多样化的影响效应。数据来源涵盖社会保障署（Social Security Institution, SSI）统计年鉴与土耳其统计研究所（Turkish Statistical Institute, TURKSTAT）的官方资料。
就业数据取自社会保障署，涵盖4-a类参保雇员信息，按照NACE Rev.2行业分类标准进行划分。4-a类参保雇员主要代表私营部门劳动者，因带有就业保障的公共部门雇员不在该类别覆盖范围内。这一区分至关重要：公共部门雇员在很大程度上不受经济冲击的影响，而私营部门就业更能准确反映劳动力市场的脆弱性及其对冲击的响应。本研究遵循Martin等人（2016）提出的方法论，依托该数据计算基于就业的韧性指标。
鉴于Eraydın（2016）所指出的土耳其存在严重的非正规就业问题，研究同时纳入GDP数据作为经济韧性的补充衡量指标。省级层面的GDP数据同样按照NACE Rev.2行业分类标准划分，取自土耳其统计研究所，与就业数据结合以全面呈现区域韧性的整体状况。
除GDP与就业数据外，研究还利用省级出口数据测算土耳其省级层面的相关多样化与非相关多样化指数。这类数据按国际贸易标准分类第三次修订版（SITC Rev.3）进行分类，同样取自土耳其统计研究所。
为确保分析的稳健性并剥离相关多样化与非相关多样化的独立影响，研究纳入了多项控制变量：无社会保障雇员占比（SocS）、对欧盟出口额（ExEU），以及用于反映土耳其东西部发展差异的虚拟变量（CrossB）。
无社会保障雇员占比（SocS）作为非正规就业普及程度的代理变量，是土耳其劳动力市场的典型特征。非正规就业由于难以获得社会保障机制且非正规企业生产率普遍偏低，可能加剧经济脆弱性；但在正规部门收缩时，非正规就业可创造就业岗位，从而在经济下行期提供灵活性并发挥缓冲作用。
对欧盟出口额（ExEU）作为土耳其最大的贸易伙伴，欧盟市场的相对稳定需求可通过提供可预测的出口收入助力经济韧性，但土耳其对欧盟的贸易依赖也会带来潜在脆弱性，尤其在经济不稳定时期。
最后，研究构建虚拟变量（CrossB）以反映土耳其东西部在经济与社会多维度的发展差异。该变量将土耳其东部与东南部13个与邻国开展跨境贸易的省份赋值为1，其余68个省份赋值为0。这13个省份的跨境贸易为其扩大出口规模提供了额外机遇，进而有助于提升该地区的福祉与收入水平。在基于出口数据测算相关多样化与非相关多样化指数时，这一区分对理解区域经济结构与韧性的差异尤为关键。
为进一步探究上述动态机制，模型还纳入了该虚拟变量（CrossB）与相关、非相关多样化指数的交互项。